Mock Interview Platform for Job Hunting

I re-ran the full suite on Gemma 3 1B and the results from earlier hold. Nothing is committed yet.

Gemma 3 1B (q4, Chrome's WebGPU on your M4, 16 GB):

• Follow-ups: 8 of 12 were usable, and they're the same 8 lines word for word as Run 3. The same 4 fell back to written lines. Each took 1.0 to 1.5 s.
• Reactions and tips: still usable. The tips never say "you", though; they all start "Focusing on…".
• Judging and code review: it's still wrong on all four. On the rambling answer it marks every STAR part false, then its own tip says the situation was described. It invents bugs in both code samples and misses the real one.
• First load: 242 s including the download (266 s last time).

I added this as Run 4 in docs/MODEL-TESTS.md. I served the eval page with Python rather than npx serve, because serve isn't installed and npx would have downloaded it. The config is in .claude/launch.json.

Loading Gemma 4 E2B: the normal text-generation pipeline works as it is in transformers.js 4.3.0, so the eval page needs no changes. The library sees that the model is multimodal and loads only the text parts: embed_tokens_q4f16 (1.59 GB) plus decoder_model_merged_q4f16 (1.52 GB), 3.11 GB in total. It skips the vision and audio encoders. The model card loads it differently (Gemma4ForConditionalGeneration plus a processor), but that's only needed for images or audio. Thinking mode stays off unless the prompt includes <|think|>.

Two things I noticed:

• PLAN.md talks about speed on an M2 Pro, but this machine is an M4, which is also what Run 1 used. Is the M2 Pro your friend's laptop? If it is, my timings here will be faster than what they'll see.
• The model card lists Gemma 4 under Apache 2.0. The licence item in your checklist says "Gemma terms", which only covers Gemma 3.

Can I download Gemma 4 E2B? It's onnx-community/gemma-4-E2B-it-ONNX, q4f16 text parts, 3.11 GB from Hugging Face. Like the 1B, it isn't cached, so every re-run downloads it again.

Gemma 4 E2B loaded with the normal text-generation pipeline, so the eval page needed no changes. It fetched only the two text files (3.11 GB), and the first load took about 14 minutes including the download. Results are in Run 5 of docs/MODEL-TESTS.md. Nothing is committed.

How it compares with Gemma 3 1B (both on your M4):

My recommendation: Gemma 4 E2B for both the live interview and the review, with Gemma 3 1B as a light option for weaker laptops. I expected to recommend 1B live and E2B for the review. But on the M4, E2B asks better follow-ups at the same speed. It's the only one that asks what the candidate did "personally", and it handles the short answers and the "next role" question where 1B pretended to be the candidate. Using one model also means one download instead of two (3.1 GB rather than about 4 GB in total). The cost is the longer first load. Once the model is cached on disk, the way your package already caches its models, that's a one-time wait.

Things this result depends on:

• STAR parts stay computed by code. Neither model can judge them.
• The guard needs two small fixes to get the full value from E2B. It should accept a question that ends in "." or is an instruction like "Describe the steps…". The reaction check also needs to reject new questions: in tough mood, E2B re-asked the opening question as a statement, and the guard let it through.
• Not measured yet:
  • The actual review jobs: what's missing compared with the sample answer, and rewriting the weakest answer.
  • Load time when the model is already cached.
  • Memory with Whisper, Kokoro and the avatar loaded at the same time.
  • Speed on your friend's M2 Pro. It has more memory bandwidth than your M4, so it's unlikely to be slower, but that's a guess. How much RAM it has matters too.

If you agree on E2B for both, I'd add test cases for those two review jobs and fix the guard next.

I've written the two-mode decision into docs/PLAN.md (models table, who does what, report section) and into the "Decisions so far" list in docs/MODEL-TESTS.md:

• Heavy: Gemma 4 E2B does both the live interview and the review (3.11 GB).
• Light: Gemma 3 1B does the live interview (859 MB).
• Only the chosen mode's model is downloaded. The other is fetched only if the candidate switches mode.
• In both modes, code computes the STAR parts and every score.

Nothing is committed yet.

Two things to decide before I build the mode picker:

1. What does Light mode show after the interview? Gemma 3 1B got both code reviews wrong, so it can't do the deep review. I'd suggest Light shows the normal report: code-computed scores, charts and the 1B's one-line tips. A "Get deep review" button would then download Gemma 4 E2B (with the 3.1 GB size shown on the button) only if the candidate asks for it. The other option is that Light simply has no deep review.

2. Which mode is the default? Heavy needs a browser feature called shader-f16 (the half-precision maths q4f16 relies on). Without it, Heavy can't run, so the app should drop to Light automatically. I'd suggest defaulting to Heavy, and suggesting Light when that feature is missing or the browser reports under 8 GB of memory. The candidate can always switch.

I've added this to docs/PLAN.md:

• Home page: the candidate picks Light or Heavy there. It's now first in the P0 list.
• Fallback: if the system can't run Heavy, the app switches to Light and tells the candidate why.
• What "can't run Heavy" means: either the browser's GPU support lacks shader-f16, which Heavy's q4f16 format needs and Light's q4 doesn't, or Gemma 4 E2B fails to load, for example from running out of memory.
• Open decisions: the Gemma 4 test is marked done.

The question about what Light mode shows after the interview is still open, so I've listed it as open decision 2 in the plan. The two options are no deep review at all, or a "Get deep review" button that downloads Gemma 4 E2B (3.11 GB) only when pressed. You can decide it whenever we get to the report.

The doc changes from this session aren't committed yet: MODEL-TESTS.md runs 4 and 5, and the PLAN.md updates. Should I commit them? The commit would have no co-authored-by line, and I won't push. I'd leave out .claude/launch.json (my local eval-server config) and the .entire/ folder unless you want them in.

I've written the breakdown to docs/TASKS.md: 9 phases, each split into steps you can check off. Each step says how we'll know it works, and we'll do them one at a time.

How the two bug workarounds fit in, based on your package's code:

• Whisper cut-off: passing onTranscribe stops the package downloading its own Whisper. So in step 2.3 the app runs the same Whisper base model in its own worker with chunk_length_s, and nothing gets downloaded twice.
• Stuck on "thinking": step 2.2 tries the possible fixes and keeps the one that works in a single wrapper, so it's easy to delete once your fix is published.

The steps that need your go-ahead (the eval downloads, creating the GitHub repo, pushing, deploying) are marked "ask before" in the file.

The first step is 0.1, committing the docs: MODEL-TESTS.md, PLAN.md and the new TASKS.md, with no co-authored-by line and no push. Should I go ahead with that?

Yes, 0.7.0 fits the app, and I didn't find anything in it that needs another fix. I checked the published build itself, not just the changelog. Nothing in the project has changed: the tarball is unpacked in the scratchpad only.

Both bugs are fixed in 0.7.0:

• Answers over 30 s: Whisper is now called with chunk_length_s: 30, stride_length_s: 5. In 0.6.0 the call had neither.
• Stuck on "thinking": any empty reply from onSubmit now ends the turn and the hook goes back to idle, ready for the next bit of speech. That covers undefined, null, '' and a stream that closes with no text. If the candidate is already talking again when the empty reply lands, they keep the floor. This is exactly what we need for collecting one answer across several pauses.

Two additions save us work:

• onSubmit(text, { speechMs }): how long the candidate actually spoke in that stretch, not counting the silence before or after. That gives the pace metric (step 5.1) directly. For an answer spread over several pauses, we add up the stretches.
• react-ai-voice-avatar/model-cache: the package's own disk cache (OPFS), built to be used inside a worker. Step 1.4 shrinks to a few lines in the Gemma worker instead of copying cache code across.

Unchanged and fine:

• Kokoro is still fixed at fp32 in the code (WebGPU, falling back to WASM, still fp32).
• Passing onSubmit still skips the package's own LLM download.
• No breaking changes. It accepts our transformers.js 4.3.0, React 19 and three.js versions.

One small thing on your side: the CHANGELOG on GitHub main still says "0.7.0 (unreleased)", while npm's copy says released. The release commit may not be pushed yet, and it's worth fixing before the post links to the repo.

What changes in the task list if we upgrade:

• 2.2 and 2.3 become "check the fix works" instead of workarounds. 2.3 no longer needs our own Whisper worker.
• 1.4 uses createModelCache().
• 5.1 uses speechMs for pace.
• 8.2, removing the workarounds, goes away.

Can I upgrade to 0.7.0 with npm install react-ai-voice-avatar@0.7.0? That downloads about 6 MB unpacked plus any new dependencies. After that I'd update TASKS.md as above.

The app is now on react-ai-voice-avatar 0.7.0, and npm run build still passes. Nothing is committed yet.

What changed:

• package.json and package-lock.json now point at 0.7.0. The lockfile change is only the package's own entry.
• npm installed 88 packages that the lockfile already listed but were missing from node_modules. They're dependencies of kokoro-js. Nothing new was added to the dependency list.
• docs/TASKS.md:
  • 2.2 and 2.3 are now checks that the 0.7.0 fixes work, not workarounds.
  • 1.4 uses createModelCache().
  • 5.1 uses speechMs for pace.
  • The old "remove the workarounds" step is gone.
  • 0.1 now includes the upgrade.
• docs/PLAN.md: the package-fixes note now says they shipped as 0.7.0.

The 4 "high" npm audit warnings:

• They're all one issue: kokoro-js pulls in an older transformers.js, which depends on sharp (a Node image library with libvips/libheif CVEs).
• They were already there before the upgrade; the lockfile at HEAD has the same chain.
• sharp only runs under Node and isn't in the browser bundle, so the deployed app isn't affected.
• npm says no fix is available. The real fix would be in your package or upstream in kokoro-js, not in this app. I'd leave it.

Next is step 0.1: commit the docs and the upgrade together. The files are MODEL-TESTS.md, PLAN.md, TASKS.md, package.json and package-lock.json. There'd be no co-authored-by line and no push, and I'd leave .claude/ and .entire/ out. Should I commit?

Committed as 50ecef9 "Initialise project", with no co-authored-by line and nothing pushed. It includes MODEL-TESTS.md, PLAN.md, the new TASKS.md, package.json and package-lock.json. .claude/ and .entire/ are still untracked.

Next is step 0.2, the app shell:

• Replace the Vite starter with the home, setup, interview and report screens, plus a small state to move between them.
• Add the cross-origin isolation headers to the dev server, so it behaves the same as Render will.
• Check by clicking through the screens and running npm run build and npm run lint.

I'll tick 0.1 in TASKS.md as part of that step's commit. Should I start 0.2?

Step 0.2 is done: the four placeholder screens work end to end, and the voice-only option is on the setup screen. Lint and build pass, there are no console errors, and nothing is committed yet.

UX rules: they're in docs/UX.md, and TASKS.md now says every step follows them. Two places in the plan contradicted them, so I changed them:

• When the download starts: step 1.6 said nothing downloads until Start. Now picking a mode on the home page starts the download, and the setup screen shows the progress.
• When an answer ends: PLAN said after 2.5 s of silence. Now it ends on "I'm done" or after a long pause. The exact length gets tuned at step 4.3, the first full interview.

What I built:

• Screens: home (device check and mode choice), setup (download, display choice, interview options, mic explanation), interview and report. They're switched by a small app state, src/app/state.ts.
• Interview screen: the layout follows UX.md: one state in words, the question, "What I heard", and buttons for I'm done, Repeat question, Skip and End interview. End interview doesn't ask for confirmation yet.
• Video interview / Phone screen: a choice on the setup screen, with video selected by default. The avatar display is lazy-loaded and builds as its own chunk.
• Privacy note: in the footer on every screen.
• Styles: calm, plain styling in light and dark, a visible focus ring, and reduced-motion support.
• Cross-origin isolation headers: added to the dev and preview servers.
• Cleanup: I removed the Vite starter files.

Checked in the browser, keyboard only:

• The page is cross-origin isolated.
• I went through every screen with only the keyboard, and focus lands on the heading each time.
• The avatar chunk loads only when a video interview opens. When Phone screen is picked, it's never requested.

Two things need your decision:

1. Scores vs "no made-up scores or percentages." PLAN.md still lists Fluency, Structure, Conciseness and Pace scored out of 100, each with its formula shown. Formulas over measured numbers aren't made up, but a score out of 100 is still a score. I'd drop them and show only what was measured (seconds, words, words per minute, filler counts, STAR parts present) plus quotes from the answers. Should I take them out of the plan, or keep them with the formulas shown?

2. One engine for both displays needs a change in your package. <AiVoiceAvatar> runs its own copy of the hook inside, and the 3D view that would take a hook's output isn't exported. Each hook instance also owns its workers and terminates them on unmount. So there are two ways to do it:

   • Change the package (my recommendation). Export the avatar view so it takes the headless hook's return value, for example <AiVoiceAvatarView voice={useAiVoiceAvatar(...)} /> from the main entry. The app then runs one hook from setup onward. The models load once, and switching between video and phone only swaps the display.
   • Work around it in the app. Phone screen uses the headless hook and video uses <AiVoiceAvatar>, both fed the same interview logic. The catch: switching display on the setup screen would restart loading, and lose whatever model file is half-downloaded.

   This is only needed at step 2.1, so phase 1 can go ahead either way.

Should I commit 0.2? The commit would include UX.md, the docs changes, the new screens and the deleted starter files, with no co-authored-by line. I'd leave .claude/ and .entire/ out again.

The workaround and the glass design are in, and I checked both in the browser. Your package isn't touched, nothing is committed, and lint and build pass.

What the OPFS check found:

• Whisper and Kokoro are cached in OPFS by both of the package's workers. Each file is written in full first, then a small marker recording its size is written next to it. A file is only reused if its marker exists and the size matches. So a reload mid-download loses only the file that was downloading; finished files are kept.
• The Silero VAD model and the ONNX runtime files don't go through OPFS. They load from jsdelivr and rely on the browser's normal cache. They're small, but it matters for offline use and the privacy meter. Your package's vadAssetPath and onnxWasmPath options let us host them ourselves, so I added that to step 6.1.
• The app's own Gemma worker will use the same cache through createModelCache() (step 1.4).

Engine workaround:

• Setup: Video interview or Phone screen is now the first choice, with video preselected. Nothing loads until they press Continue. After that the choice is shown as fixed text: "To change this, go back to the home page."
• One engine, mounted once: EngineHost is mounted at the app level when Continue is pressed. It stays hidden on setup and becomes the stage on the interview screen. It's removed after the interview, or if they go back to the home page.
• Checked in the browser:
  • The engine is the same DOM node on setup and in the interview, so it never remounts.
  • The video code loads only after Continue with video picked. A phone-screen run never requests it.
  • Ending the interview removes the engine.
  • Every screen works with the keyboard alone.
  • There's no horizontal scroll at 375 px wide.

Design (UX.md now has a "Look and feel" section):

• Theme: dark gradient background with one accent colour, a soft blue (#8fb4ff).
• Radius scale: 8 / 12 / 20 px plus pill. Every radius in the CSS uses one of these.
• Glass: one glass panel per screen. The avatar's stage is a solid panel, so nothing is blurred over it.
• Fallbacks: solid panels when backdrop-filter isn't supported or the user prefers reduced transparency.
• Motion: only short colour and opacity transitions, about 160 ms, switched off with reduced motion.
• Contrast: over the real background, everything is at least 6:1. Body text is 14:1, muted text 7.2:1, the state chip 6:1 and the primary button 9:1. Over pure white, muted text would drop below AA unless the glass were about 90% opaque, which kills the glass look. Glass only ever sits on our own background, so I kept 72%. I wrote that limit into UX.md: the opacity goes up if glass ever covers anything bright.

The question about scores out of 100 vs "no made-up scores" is still open. It only matters when we get to the report in phase 5.

Should I commit 0.2 now? It would include UX.md, the docs updates, the screens, EngineHost, the styles and the starter-file removal, with no co-authored-by line and nothing pushed.

Scores are out of the plan, and everything so far is committed as bccb1ec "Add app shell, engine host, UX rules and glass design". There's no co-authored-by line and nothing was pushed; .claude/ and .entire/ are still untracked.

What the report now shows (PLAN.md, UX.md, TASKS.md phase 5):

• Only measured numbers: time per answer, words, words per minute and filler words by type. Each one says how it was measured.
• Their answers quoted, with fillers highlighted and the part past the target time shaded.
• Plain comparisons where they help, like "Most behavioural answers aim for about 2 minutes; this one was 3 min 40 s."
• Charts of the measured numbers only.
• UX.md now says: no scores out of 100, no ratings and no percentages, even ones with a formula behind them.
• The old Scores step (5.2) became "Plain comparisons". The progress history in 7.1 keeps measured numbers only.

STAR:

• STAR is out of the report for now. Run 5 already showed Gemma 4 E2B marking all four parts present in a rambling answer, and the plan says so.
• Step 5.5 adds more STAR test cases. If E2B passes, STAR parts only appear as "possible gaps" in plain words, never as a grid or a number.
• I wrote that we agree the pass bar before that run, so the bar isn't picked after seeing the results.
• Missed key points: these were matched by keywords in code, and you didn't list them. I put them under the same rule, as "possible gaps" or left out, because keyword matching isn't a measurement either. Tell me if you'd rather keep them.

Other doc fixes:

• MODEL-TESTS.md said "Gemma 3 1B is the live interviewer". Now it's whichever model the chosen mode uses.
• The caching note now points to 0.7.0's model-cache.

Next is step 1.1, the device check:

• Check for WebGPU, a usable adapter and shader-f16 on the home screen.
• If WebGPU is missing, say so plainly.
• If shader-f16 is missing, disable Heavy and show why.

Should I start 1.1?

Step 1.1, the device check, is done and checked in the browser. Lint and build pass, and nothing is committed yet.

How it works:

• The check runs once when the app opens (src/app/device.ts, src/app/useDeviceCheck.ts).
• In order, it looks for: a secure page (WebGPU only works on https or localhost), WebGPU itself, a reachable graphics chip, a real chip rather than a software fallback, and shader-f16 for Heavy.

What the home screen shows:

• While checking: "Checking what this browser can run…", with both mode buttons disabled.
• Both modes available (your M4): "Ready. This browser can run both modes on your graphics chip."
• No shader-f16: "Ready for Light mode", plus the reason Heavy isn't available. The Heavy card is disabled and its reason is attached to the button for screen readers.
• Can't run at all: both cards are disabled, with a plain message saying what to do:
  • no WebGPU: use a recent Chrome or Edge;
  • chip not reachable: turn on hardware acceleration, update, reload;
  • software GPU only: this device is too slow;
  • not https: open the https link.
• Styling: the notice is neutral, a left border with no warning colour, so there's still only one accent. Disabled cards get a dashed border instead of fading, because the faded version made Heavy's reason unreadable.

How I tested the failure cases: a dev-only URL switch, ?device=no-webgpu, no-adapter, software-gpu or no-f16, fakes a weaker device. I went through all four plus the real M4 result. The switch is stripped from the production build; I checked dist and it isn't there.

Next is step 1.2: the full download list with sizes on the home page (VAD, Whisper, Kokoro, the mode's Gemma, and the avatar for video), with a total per mode. Should I commit 1.1 first, then start 1.2?

Step 1.2 is done. The home page now lists everything a first visit downloads, with real sizes, before anything starts. Lint and build pass, and it's checked in the browser at desktop and phone widths. Step 1.1 is committed as 6aab99f; 1.2 isn't committed yet.

What a first visit downloads:

The mode cards now show these totals ("About 1.6 GB the first time"). Before, they showed only Gemma's size, which made the download look much smaller than it is.

Where the numbers come from: file sizes from the Hugging Face and jsdelivr metadata APIs, plus a throwaway minified build to measure the 3D code. Nothing was downloaded. They live in one file, src/app/downloads.ts, which step 1.6 will reuse to show download progress.

Things that came out of measuring:

• Whisper is 295 MB, not about 150 MB. The package doesn't set a precision, so on WebGPU transformers.js loads the full-precision fp32 files. PLAN.md is corrected, and Kokoro's figure too. If you ever want it smaller, setting fp16 (147 MB) would be a package change for after the challenge.
• The runtime figure includes one estimate. About 27 MB of the 67 MB is the Gemma worker's own copy of the runtime, read from the version installed locally. I'll confirm it in 1.3, when that worker actually loads it.
• The VAD and runtime files will load under our COEP header. jsdelivr sends Cross-Origin-Resource-Policy: cross-origin, which those headers require.
• Small sizes are uncompressed. The runtime and 3D code arrive compressed, so they transfer smaller than listed. The model files are the bulk and don't compress further, so the totals are about right.

Layout fix: at phone width the three-column table squeezed into 283 px. Each row now shows the model name with what it's for underneath, and narrow screens get tighter padding. Nothing overflows at 375 px.

Should I commit 1.2 and start 1.3, the Gemma worker?

That one match is the local Vite bundle of transformers.js (/node_modules/.vite/deps/...), not a model download. Nothing has been downloaded from Hugging Face.

The Gemma worker code for 1.3 is written. I haven't marked the step done, because its real check needs a model download, which I'm asking about below. Nothing is committed yet.

What's built:

• src/gemma/protocol.ts: the model per mode (Light: Gemma 3 1B q4, Heavy: Gemma 4 E2B q4f16) and the messages between page and worker.
• src/gemma/gemma.worker.ts:
  • loads only the chosen mode's model on WebGPU, through the same text-generation pipeline as the evals, and reports per-file download progress;
  • runs a one-token warm-up after loading, so the GPU code is compiled before the first real reply rather than in the middle of the interview;
  • streams tokens with greedy decoding;
  • can be stopped mid-reply.
• src/gemma/GemmaClient.ts: the page-side wrapper. load(mode, onProgress), generate(messages, { maxNewTokens, onToken }), stop() and dispose(), one reply at a time.
• Dev-only test panel at ?dev=gemma: pick a mode, Load, Generate, Stop. It's stripped from the production build; I checked dist.

Checked so far, without downloading anything:

• Type-check, lint and build pass.
• In the browser, the worker starts, imports transformers.js, and answers a request sent before loading with "Gemma is not loaded" in 165 ms.

What's left is an actual reply from each model, and that means downloading them: Light is 880 MB and Heavy 3.13 GB. Until step 1.4 adds the disk cache, every page reload downloads the model again.

I'd do 1.4 (the OPFS cache) before downloading. It's a few lines in this worker using your package's createModelCache(). Then each model downloads once, and the same download covers both checks:

• the 1.3 check, a reply in each mode;
• the 1.4 check, a reload makes no model requests and the load from disk gets timed.

It also saves the re-downloads in every later step that loads Gemma.

So: can I add the cache first, then download Light (880 MB) and Heavy (3.13 GB) to test both steps? Or would you rather I test 1.3 now without the cache?

Steps 1.3 and 1.4 are done for Light. I downloaded Gemma 3 1B (880 MB) once, and from now on it loads from disk. Lint and build pass; nothing is committed yet.

Gemma 3 1B in the app's own worker (M4, Claude's browser pane):

I added the cache before downloading, which wasn't in your instruction. It's step 1.4, a few lines using your package's createModelCache(), and it meant the 880 MB came down only once. A reload now loads in 2.9 s instead of downloading again. After the reload, the cached model gave the same reply word for word as the freshly downloaded one.

Things I found:

• Heavy may not fit in this test browser. Claude's browser pane gives the app only 2.6 GB of storage, enough for Light but not for Heavy's 3.13 GB. Desktop Chrome usually allows far more. The Heavy step now checks the quota before downloading and says plainly if the model won't be kept.
• Reading from disk also shows up as progress. transformers.js reports progress while loading cached files, so the dev panel said "downloading" during the 2.9 s reload. Step 1.6 has to say "loading from this device" in that case; I noted it there.
• The runtime estimate from 1.2 is right. Gemma's worker gets its own runtime from jsdelivr (onnxruntime-web@1.31.0-dev, 26.9 MB), so the 67 MB in the download list stands.

Doc updates:

• TASKS.md: says Light first. A new phase H gathers everything Heavy: loading it with the storage check, the fallback to Light (formerly 1.5), the guard evals, the review evals and the deep review. Step 4.3 tests both video and phone with Light.
• MODEL-TESTS.md: has these numbers as Run 6.

Next is 1.6, the download progress on setup. It needs your package's engine actually loading, so it overlaps with 2.1, wiring up the hook. I'd do them together:

• mount PhoneEngine with the headless hook when Continue is pressed;
• start Gemma loading at the same moment;
• show real progress per model, telling apart "downloading" and "loading from this device".

That means a first download of Whisper (295 MB), Kokoro (326 MB), the VAD (1.8 MB) and the runtime (about 40 MB), roughly 660 MB. All of it is kept after the first time, except the VAD and runtime, which rely on the browser's normal cache.

Should I commit 1.3 and 1.4, then go ahead with 1.6 plus the phone-screen part of 2.1, including that roughly 660 MB download?

Step 1.6 is done for Light with a phone screen, and so is the phone half of 2.1. Pressing Continue now really loads the models, with real progress on the setup screen. Lint, type-check and build pass, and nothing is committed yet. Two things went wrong along the way, explained below; one of them meant downloading Gemma again.

What works now:

• Continue on Phone screen starts your package's headless hook (Whisper and Kokoro) and the Gemma worker together.
• Each model shows its real state: Waiting, "Downloading, 120 MB of 295 MB", "Loading from this device" or Ready. The setup screen tells a download from a cache read by checking the shared OPFS store for the model's weight files before loading.
• Start interview stays disabled, with a short note, until every model is ready.
• Screen readers hear only "1 of 3 models ready" style changes, not every percent.
• With everything already on the device: Continue to "Everything is ready" in 3.7 s.
• First download of Whisper and Kokoro went fine; both are now kept in OPFS.

Problem 1, fixed: Gemma's progress bar was wrong. It hit 100% after a few seconds, then seemed stuck. I'd worked out the percentage over the files seen so far, and the small config and tokenizer files finish before the 859 MB weights start. The download was actually still running in the background, sharing bandwidth with Whisper and Kokoro. Progress is now measured against the model's known size and held at 99% until Gemma reports ready.

Problem 2, not explained: Gemma's cache entry vanished. Between the 1.4 test and this step, the weights file and tokenizer disappeared from OPFS. That's why Gemma downloaded again: 880 MB more than the roughly 660 MB I asked you about.

• Ruled out: transformers.js only deletes cache entries through its explicit clear_cache call, and your package's cache only clears an entry right before rewriting it.
• Since then it's held up: I re-ran the whole flow with logging on every cache call, and the entry was stored, survived a reload, and nothing was deleted.
• Next time: dev builds now log every Gemma cache call to the console as [Gemma cache], so if it happens again we'll see exactly what removed it. It's noted as a watch item in TASKS.md.

Smaller things:

• transformers.js also keeps the Gemma worker's ONNX runtime in the same OPFS store, so that's kept between visits too.
• In dev, React's StrictMode starts two Gemma workers and immediately stops the first one. That doesn't happen in production.

Still to do in 2.1, the video part: VideoEngine with <AiVoiceAvatar> and the avatar's progress row. Until then, choosing Video interview leaves Start disabled.

Should I commit this and move on to the video part of 2.1? That downloads the avatar file (about 4.5 MB) and the 3D code. Whisper and Kokoro should load from disk, but the video component runs its own copy of the engine, so I'll check that it reuses the cache.

The fix builds and lints cleanly. I haven't tested it, because a test means downloading again, and I'd rather ask first given what's happened. I've stopped here; nothing is committed since the last commit.

What I found:

1. The video engine never started. Fixed in code, not yet tested. While the engine host is hidden on the setup screen it used display: none, so the 3D canvas had zero size, and react-three-fiber doesn't mount the avatar (or its copy of the engine) until the canvas has a size. Whisper, Kokoro and the avatar stayed on "Waiting" for 40 s. Now the hidden host keeps its real size off-screen, invisible to screen readers, and the canvas only renders frames on demand until the interview screen shows it.

2. The model cache is being wiped in Claude's browser pane. This time everything went: Whisper, Kokoro and Gemma. The first incident earlier fits the same pattern. The evidence points to the pane, not our code:

   • Its storage quota is 2.6 GB, on a disk with 43 GB free. Normal Chrome allows roughly 60% of the disk.
   • Usage reads 2,400 MB while the files on disk add up to only 21 MB. That behaves like memory-backed, incognito-style storage, which Chrome evicts as a whole when it goes over quota.
   • Storage isn't persisted (navigator.storage.persisted() is false).

   The cost: Gemma came down a second time earlier, and a third download had started before I stopped it at about 125 MB. Whisper and Kokoro are gone and would download again. That's more than you approved, sorry.

What I'd suggest:

• Test caching and video in your own Chrome, not this pane. In this pane the cache can't be trusted, and every test risks another 1.5 GB. Either you open http://localhost:5173 in Chrome yourself, or I drive your Chrome with Claude in Chrome if you'd like that. A first visit downloads about 1.5 GB (Light plus video); a reload should then show "Loading from this device" for everything.
• Harden the app for your friend's browser. When loading starts, ask the browser for persistent storage (navigator.storage.persist()), and check the quota before downloading. If it's too small, as in incognito, say plainly that the models won't be kept and will download again next time. It's a small change, and it's the same check phase H already needs for Heavy.

How do you want to test: your Chrome yourself, me driving your Chrome, or this pane anyway (another roughly 1.5 GB with no guarantee it stays cached)? And should I add the persistent-storage request and quota check now?

onSubmit is now wired to Gemma for both the phone screen and the video interview. Type-check, lint and build pass. I haven't heard it run: that needs a microphone, and this browser pane keeps wiping the models. So please test it in your Chrome. Nothing is committed yet; this includes the video-engine fix you already tested.

How a turn works now:

1. Start interview opens the mic as part of the click, since browsers need a user gesture for the mic and audio. The interviewer then speaks an opening question: "Tell me about a project you're proud of."
2. You speak. When you pause, Whisper's text goes to onSubmit.
3. onSubmit passes it to the Gemma worker, which streams the reply back. Your package starts speaking with Kokoro as soon as the first sentence is ready.
4. If you talk over it, the package stops speaking and the app stops Gemma generating the rest.

What changed:

• src/engine/voiceStore.ts: a small shared store, so the interview screen gets status, captions, mic errors and controls from whichever engine is mounted, phone or video.
• GemmaClient.stream(): turns Gemma's token stream into the async iterable your package speaks sentence by sentence.
• src/interview/placeholderBrain.ts: a stand-in interviewer using the eval persona and conversation history. Phase 3 replaces it with the real engine.
• Interview screen: a live state (Listening / Thinking / Speaking), what the interviewer said, what Whisper heard, and a plain message if the mic is unavailable.
• Video engine: gets the same onSubmit. Controls come from the <AiVoiceAvatar> ref; gestures are off when reduced motion is set.

What to try in Chrome (http://localhost:5173, with npm run dev running):

1. Light → Phone screen → Continue → wait for Ready → Start interview. Allow the mic and answer the opening question. You should hear a short follow-up about what you said.
2. Talk over the interviewer while it's speaking. It should stop.
3. Answer one question for more than 30 seconds without stopping. The whole answer should appear under "What I heard"; that's your 0.7.0 fix.
4. Repeat with Video interview. The avatar should lip-sync.

Limits until phase 3:

• Every pause gets a reply. Collecting one answer across several pauses is step 3.2.
• Gemma's text goes straight to the voice, with only markdown and quote marks removed. The guard comes in step 3.4.
• I'm done, Repeat question and Skip don't do anything yet.
• There's no separate mic check: the setup screen's explanation stands in for it until step 2.4.

Tell me what you hear. If it works, I'll commit the video engine, its fix and this wiring together.

The question bank (step 3.1) is in src/interview/bank.ts, and the checks pass. Nothing is committed yet.

What's in it:

• 46 questions: 10 behavioural and 6 HR for every track, plus 10 technical each for frontend, backend and ML.
• Each question has: the levels it suits, what the interviewer is really checking, 2–3 key points with phrases for the code to match, what a strong answer covers, and two written follow-ups to use when the guard rejects Gemma's line.
• pickQuestions({ round, track, level, count }) returns a shuffled set for one round, or a full loop: 2 behavioural, 2 technical and 1 HR.
• Levels: harder questions are mid and senior only, for example rate limiting, idempotency, transformer attention and helping a teammate grow.

Checked with a script:

• every id is unique;
• every follow-up is a question;
• every track and level gets at least 4 questions per round;
• a full loop always has the right mix and never repeats a question.

Backend interns had only 2 technical questions at first, so I opened indexes and transactions to all levels.

Key-point matching on the eval answers:

• On the strong STAR answer, all three points matched.
• On the "we did…" answer, it flagged "their own part" as missing, which is exactly when the engine should ask what they did personally. That's the job these key points have: choosing the follow-up angle.
• The matching is coarse: "much faster" counts as a result. That's fine for picking an angle, and it's why they can only ever appear as "possible gaps" in the report.

Should I commit, then do 3.2, the interview engine? It's plain code that drives the interview's turns:

• greeting, ask, then collect the answer across pauses until "I'm done" or a long pause;
• follow-up, reaction, next question, closing.

3.2 is also where the empty-reply fix (2.2) gets checked, and I'll make the engine testable without a microphone.

I've added 10 system design questions as a new round, so the bank now has 56. Type-check, lint and the bank checks pass. Nothing is committed yet.

The questions (src/interview/bank.ts):

How they work:

• What a strong answer covers: each sample answer spells out a spoken walk-through, since there's no whiteboard: clarify requirements, propose a simple design, then talk scale and trade-offs.
• Key points pick out the usual weak spots: requirements and scale, how codes are generated, caching, double booking, offline users, cold start.
• The written follow-ups are classic probes, like "Two people click the same seat at the same moment. What happens?" or "What happens when someone with ten million followers posts?"
• Separate round: system design is its own round, system-design, because the answers run much longer than a technical question and the follow-ups are different.
• Levels: interns don't get system design; juniors get 3 questions per track, mid and senior 6–7.

Doc updates:

• PLAN.md: the new round in the setup options, the bank type and the targets.
• TASKS.md: the new count in 3.1, and step 4.1 now lists system design as a round choice.

Two choices for you, both easy to change later:

1. Full loop: it's still 2 behavioural, 2 technical and 1 HR. Should mid and senior full loops include one system design question, swapped in for one of the technical ones?
2. Answer length for system design: I'd suggest a target of about 5 minutes per answer, against 2 minutes for behavioural, and a longer "long pause" before the answer counts as finished, since people think out loud more here. Does that sound right?

Then: should I commit and start 3.2, the interview engine?

Committing first:

Good call; let's pin this down before I go further. Here's where system design stands, and what I'd keep or cut.

Already written, not committed or tested:

1. Data: each of the 10 system design questions has a short set of facts (scale, users, constraints) and 4 probes in order: high-level design, deep dive, then two on scale and trade-offs.
2. Engine logic (in engine.ts, about 30 lines specific to system design):
   • A clarifying question gets the facts. If the candidate asks something like "how many users?" or "can I assume…", the interviewer reads that question's facts, with a short lead-in such as "Sure."
   • Otherwise it moves on: the interviewer asks the next probe.
   • It wraps up once the probes are used up, or after 8 exchanges or 12 minutes, whichever comes first.
3. A longer pause: 7 s before an answer counts as finished, against 5 s for other rounds.

What I'd cut, to keep the scope small:

• No Gemma in system design. Facts and probes are written lines, so nothing can invent numbers, and it works the same in Light and Heavy.
• No judging of the design: no "possible gaps" and no review of the architecture. The 1B model can't judge it, and Heavy's review stays phase H scope.
• Tighter limits: 4 probes and at most 2 clarifying answers, so 6 exchanges and about 10 minutes, then wrap up. That's 2 fewer exchanges and 2 fewer minutes than what I wrote.
• Not in the full loop. It's only available when "System design" is picked as the round.
• No whiteboard, diagrams or typed input. It's spoken only.
• Report: the conversation as exchanges (what the interviewer asked, what they said), with time and words per exchange. Same rules as everything else: no scores.

What it costs from here: I tighten the limits, and the engine's test script gets one system design run: a clarifying question, the probes and the wrap-up. No other new work.

Does that scope work for you: written facts and probes only, at most 6 exchanges or about 10 minutes, no judging, not in the full loop? If yes, I'll tighten the limits, finish 3.2 (wire the engine into the app and test it without a mic), and record this scope in PLAN.md.

The interview engine (3.2), the follow-up angle rules (3.3) and the prompts and guard (3.4) are built and replace the placeholder interviewer. Type-check, lint, build and 40 checks run without a mic all pass. Nothing is committed yet: I'd like you to hear one interview in Chrome first.

System design is parked in PLAN.md with the scope we agreed: conversational, written facts and probes only, at most 2 clarifying answers and 7 exchanges (about 10 minutes), no judging, and not in the full loop.

How an interview runs now:

1. Small talk: "Hi, I'm Ananya. Thanks for joining. Before we start, how's your day going?"

2. Each question is asked. Your answer is collected across pauses until you press I'm done or stay quiet for 5 s after your last words. That's about 6.5 s of real silence, because Whisper's transcript arrives about 1.5 s after you stop. Starting to talk again cancels the countdown. Every stretch of speech gets an empty reply, so the package keeps listening; that's your 0.7.0 fix doing its job.

3. One follow-up per question. Rules pick what to probe:

   • an answer under 25 words → ask for more detail;
   • lots of "we", little "I" → what did you do;
   • no outcome → the result;
   • a missing key point → that point;
   • technical → an edge case;
   • HR → what you want or value;
   • otherwise → a trade-off.

   Gemma words it with the run 3 prompt, then the guard checks it. If Gemma's line is rejected, or takes more than 6 s, a written line for that angle is spoken instead.

4. Next question: a short reaction, then the next question.

5. End of the questions: "Do you have any questions for me?", then the closing, then See your report.

6. Buttons: I'm done, Repeat question, Skip and End interview all work.

The new guard on the real lines from runs 4 and 5:

• Gemma 4 E2B: 12 of 12 pass. The old guard passed 8, rejecting good questions over a missing "?". Question-word lines ending in "." get a "?"; instructions like "Describe the steps…" are kept as they are.
• Gemma 3 1B: 8 of 12, the same 8 good lines as before, now with "That's a good start" removed. The 4 role-play or non-question lines all fall back to written lines.
• Reactions: a "reaction" that's really a new question ("Tell me about a time…") is rejected.

Please try it in Chrome (npm run dev, then Light → Phone screen → Start). For now it runs a full loop for a junior frontend developer; to try a single round, add ?round=behavioural, technical or hr to the URL. Worth checking:

1. Pause for 2–3 s mid-answer, then carry on. It should stay one answer under "What I heard".
2. Give a short answer, then a "we did…" answer. The follow-ups should ask for detail, then what you did.
3. I'm done, Repeat question, Skip and End interview.
4. Whether 5 s feels right before it moves on, or whether it should be longer or shorter.

If it sounds right, I'll commit and move to 3.6, recovery: silence, "repeat that", "what do you mean", "I don't know", garbled audio, a lost mic, and Gemma failing mid-interview.

Committed as 4ea8ee2: the interview engine, follow-up angles, prompts, guard and session wiring. The system design scope is recorded in PLAN.md, and the placeholder interviewer is removed. There's no co-authored-by line, nothing was pushed, and .claude/ and .entire/ are still left out.

Two things are still open from my last message:

• No confirmed full spoken interview yet. That spoken run also checks 2.2, the empty reply going back to listening.
• The 5 s pause: say if it feels too short or too long and I'll change it.

Next is 3.6, recovery: what the interviewer says and does when things go wrong.

• Silence after a question: at 12 s, "Take your time. Want me to repeat the question?"; at 25 s, it moves on and marks the question skipped.
• "Can you repeat that?" or "Sorry?": it repeats the question.
• "What do you mean?": it rephrases, using what the question is checking.
• "I don't know" or "pass": one nudge, then it moves on.
• Garbled or one-word transcripts: "Sorry, I didn't catch that."
• "Can we pause?" or "Stop": it pauses or ends the interview.
• Gemma failing mid-interview: it carries on with written lines and notes it for the report.
• A lost mic or a hidden tab: it pauses, with a plain banner.

Most of this is plain code in the engine, so I can test it without a mic like the last step. Should I go ahead with 3.6?

Recovery (3.6) is done, and the architecture review is written up in docs/ARCHITECTURE.md. The review found three small fixes I'd make before the interview room step. Lint, build and 88 checks run without a mic all pass, including new ones for recovery. Nothing is committed yet. Recovery still needs hearing in Chrome; the checks don't cover the real voice.

Recovery, all said out loud:

These phrases are only checked on short stretches at the start of an answer. Real answers like "Sorry, I didn't explain that well…" or "I don't know if it was the best approach, but…" are tested and stay answers.

The architecture doc was checked against the actual imports, not the plan. It has:

• A diagram of all the pieces: the main thread, the three workers, the OPFS cache, and the networks used on the first visit only.
• A sequence diagram of one answer, pauses and follow-up included.
• A table of what's alive when.

What it confirmed:

• The interview engine stands alone: no React, audio or Gemma.
• No app code sends anything off the device: no fetch, beacons or sockets.
• One mount from setup to the end of the interview.
• Only the chosen Gemma downloads, and three.js only for video.

What the review found to fix:

1. A naming clash. src/engine/ is the voice engine, while src/interview/engine.ts is the interview engine. I'd rename src/engine/ to src/voice/. It's mechanical; nothing changes in behaviour.
2. Gemma dies with the interview. It's disposed when the report screen opens, but Heavy's deep review (phase H) needs it on the report screen. I'd move Gemma's owner up to App, so it lives from setup until you leave the report.
3. Dead state. The voice store still records captions the screen no longer reads. I'd remove them.

Should I make those three fixes, then commit 3.6, the architecture doc and the fixes together? I can also move the 88-check test script into the repo with an npm test script, so the checks can be re-run after changes.

The architecture artifact is published: Interview Room Architecture. It's private to you until you share it from the page's Share menu. I couldn't preview it before publishing, because the browser pane can't screenshot local files, so tell me if anything renders oddly.

What's on the page:

• The pieces: everything inside a "this device" boundary, with labelled arrows: screens, session, interview engine (highlighted, since it makes every decision), writer, voice engine, the Gemma, Whisper and Kokoro workers, and the OPFS cache. The only arrow crossing the boundary is the dashed inbound one for model files on the first visit.
• One answer, start to finish: a sequence diagram covering the silence timer, speech arriving in stretches, talking again cancelling the 5 s timer, then angle, Gemma, guard and the spoken follow-up.
• What's alive when: the lifetime table.
• Review: what I verified in the code next to the six fixes, each tagged with when it's due: three before the interview room (the naming clash, Gemma's lifetime, dead state), one after the challenge, one accepted, one at step 6.1.

The content matches docs/ARCHITECTURE.md, which is still uncommitted along with step 3.6. Once you've reviewed it, tell me what to change. After that, I'll make the three "before 4.x" fixes and commit everything together.

The short answer: in the current design, neither Gemma model judges the candidate's answers. Code decides what to probe, and the guards check Gemma's output, not the candidate's. If we want quality assessment, Light can't do it, and Gemma 4 E2B is only partly proven.

Intents (src/interview/intents.ts) are checked only on short stretches (10 words or fewer) at the start of an answer, so real answers that happen to contain these words stay answers:

Guards (src/interview/guard.ts) run on every Gemma line before it's spoken:

• guardFollowUp:
  • drops a line where Gemma speaks as the candidate ("Rahul: I'm…") or narrates ("He explained…");
  • removes praise ("good start", "great answer", "excellent"…);
  • drops sentences that just repeat the question or the candidate's answer;
  • needs a real question: one ending in "?", one starting with a question word ending in "." (which becomes "?"), or an instruction like "Describe…" or "Walk me through…";
  • keeps at most one short lead-in sentence plus the question, and caps the length;
  • if nothing survives, the written line for that angle is spoken.
• guardReaction: removes praise and anything that's a question or an instruction, and keeps one closing sentence. Reactions are currently written lines, so this is ready but unused.

Who judges what right now:

• What to probe: code rules (angles.ts): word count, "we" versus "I", outcome words, key-point phrase matching.
• Gemma's job: only to word that probe naturally.
• The report: measured numbers and quotes only, per your rule.

Can either model assess answer quality? From the tests so far:

• Light: no. It can word a follow-up it's told to ask, but its judgements were wrong every time, so it should never assess anything.
• Heavy: possibly, for some things. It handled code review in the two cases we tried, but it said yes to everything on STAR, so STAR stays out unless more cases pass a bar we agree first.

Four test cases aren't enough to rely on. The deep-review jobs are exactly what step H.4 tests: possible gaps against the sample answer, rewriting the weakest answer, and more STAR cases. If Heavy passes, its output goes into the report as "possible gaps" and suggestions, never as a score. Light mode gets the measured report only, unless you choose the opt-in "Get deep review" download (PLAN.md open decision 2).

The setup page (4.1) is built, with the mic check (2.4) inside it. The options now feed the real interview, replacing the junior-frontend default. Type-check, lint and build pass. I checked the layout and the rules in the browser. Nothing is committed yet. Before this I committed 3.6 and the architecture doc as 1fef213.

What the setup screen does now:

1. First step, fixed once Continue starts loading:

   • video interview or phone screen;
   • who interviews you: Ananya (her avatar, Kokoro voice af_heart) or Aarav (his avatar, voice am_michael; I checked Kokoro has it).

   The interviewer moved into this step because the avatar and voice load with the engine and can't swap afterwards.

2. Model progress, as before.

3. "Your interview", filled in while the models load:

   • Track: frontend, backend or machine learning.
   • Level: intern, junior, mid-level or senior.
   • Round: full loop (5 questions), behavioural, technical or HR. System design stays parked.
   • Number of questions: 3–5, capped by what the bank has. Backend + intern + technical only has 4, so "5" is disabled; I tested that.
   • Target answer length: 1–3 minutes, with the "about 2 minutes" comparison.
   • Mood: friendly, neutral or tough, each with a one-line description.
   • Name: optional, so the greeting uses it.

4. Microphone:

   • Before asking: says why the mic is needed and that the browser is about to ask for permission.
   • Test microphone: shows a live level meter and "Heard: …" with Whisper's text.
   • Hear Ananya's voice: plays a short line in the interviewer's voice.
   • If access is refused: says how to allow it.

How the pieces connect:

• Settings: they live in src/interview/settings.ts and reach the engine through the session.
• The mic level: it's on its own channel in the voice store, read every frame without re-rendering React. The phone-screen orb in 4.2 will use the same channel.
• Dev preview: a dev-only ?dev=setup page shows the screen after Continue with a sample loading state, so the layout can be checked without downloading. It's not in the production build.

Please try in Chrome:

• Pick Aarav with Video interview. You should see Aarav's avatar and hear a male voice.
• Run a single round, for example HR with 3 questions and a tough mood.
• Use the mic test, then Start.

The three architecture fixes are still waiting: the src/engine → src/voice rename, keeping Gemma alive through the report, and removing the unused said caption state. One correction to the review: heard isn't dead after all, because the mic check uses it now. Should I make those fixes before 4.2, the interview room (answer timer, progress dots and the phone-screen orb)? And should I commit 4.1 now?

Here's how Gemma's lifetime works today, why that's a problem for the deep review, and what I'd change.

Today:

• Who owns it: Gemma's worker is created and owned by EngineHost, the component that also holds the voice engine (Whisper, Kokoro, the avatar).
• When it's created: EngineHost mounts when you press Continue on setup.
• When it dies: EngineHost unmounts when the interview ends and the report opens. Its cleanup disposes everything, Gemma's worker included.
• Next interview: "Practice again" mounts everything fresh, so the models load again from disk (Light took about 4 s).

Why that's a problem later: the deep review in Heavy runs after the interview, on the report screen. That covers code review, possible gaps against the sample answer, and rewriting the weakest answer (phase H). By then Gemma is already gone. The same applies to Light's optional "Get deep review" button, if we build it (PLAN.md open decision 2), and to any one-line tips the report asks Gemma for.

Three ways to handle it:

What option A looks like:

• Creation: a small GemmaHost (or a hook in App) creates the Gemma worker when Continue is pressed, exactly as now. It reports progress to the same setup screen and hands the client to the interview session.
• Lifetime: it stays alive from setup through the interview and the report, and is disposed when you go home or switch mode.
• The voice engine: it still unmounts when the interview ends. That frees Whisper, Kokoro and the avatar right when Heavy's review needs room for longer prompts. On your friend's M2 Pro that headroom matters more than on your M4.
• A bonus for Practice again: if the mode is unchanged, Gemma is already warm, so only Whisper and Kokoro reload.

When it's needed: nothing breaks today, because Light doesn't use Gemma on the report yet. It becomes required at phase H. I'd still do it before 4.2: it's a mechanical move while that code is fresh, and phase H can then focus on the review prompts.

Should I go with A? If yes, I'd do it together with the src/engine → src/voice rename and removing the unused said state, then commit 4.1 and the fixes in one go.

I made both fixes and left Gemma's lifetime as it is. Everything is committed as 5ce80b9, together with 4.1. Nothing was pushed, and .claude/ and .entire/ are still left out.

What changed:

1. Rename: src/engine/ is now src/voice/, and the files are VoiceHost, PhoneVoice, VideoVoice, voiceEvents and isVoiceMounted. "Engine" now only means the interview engine (src/interview/engine.ts). Git tracked the moves as renames, so file history is kept. Type-check, lint, build and the 88 engine checks pass.
2. Unused state: the voice store no longer keeps the interviewer's sentences. It keeps only heard, which the mic check shows.
3. Gemma's lifetime: unchanged. It still ends when the interview ends. In ARCHITECTURE.md and the artifact it's marked "later", with a note that you're planning a different architecture for the deep review.

The architecture artifact is updated to version 2: new file names, and the fix list now shows the rename and the state cleanup as done, Gemma's lifetime as later.

Still open from 4.1: try the real flow in Chrome with Aarav and a single round, to hear his voice and see his avatar.

Next is 4.2, the interview room:

• Answer timer: amber near the target, red past it.
• Progress dots for the questions.
• Layout: the avatar or voice stage beside the question card, the captions and the controls.
• The phone-screen orb: glows with your voice or the interviewer's, a calm pulse while thinking, and still under reduced motion.

Should I start 4.2?

The interview room (4.2) is built and checked in a dev preview that runs the real engine with simulated speech and no models. Type-check, lint, build and the 88 engine checks pass. I haven't heard it with real voice yet, and nothing is committed.

What's on the interview screen now:

• Top row:
  • State in words: Listening, Thinking, Speaking, Paused or Finished.
  • Progress dots: filled when answered, dashed when skipped, ringed for the current question, with words for screen readers.
  • Answer timer, explained below.
• Question card: the current question, large and always on screen.
• Captions: what the interviewer last said, and what Whisper heard across your pauses. On by default, with a Hide captions toggle.
• Controls: I'm done, Pause/Resume, Repeat question, Skip and End interview.

The answer timer:

• When it counts: from your first words, so thinking time before you speak isn't on the clock. It resets for the follow-up answer.
• Colours: amber from 80% of your target, red past it. These are separate status colours, not the accent.
• Screen readers: "Past your 2 minute target" is announced once, not every second.
• Checked: with a 15 s target it went normal → amber at 0:13 → red at 0:17. In the preview I also saw the 5 s pause end an answer, then the timer restart for the written follow-up.

The phone-screen orb:

• Reacts to whoever holds the floor: your mic level while listening, the interviewer's voice while speaking.
• Other states: a slow pulse while thinking (including while Gemma words a follow-up), dimmed while paused or loading.
• Light on the GPU: only transform and opacity change each frame, driven by the mic-level channel without React re-renders. Under reduced motion it holds still and only its brightness changes.
• On phones: the stage is capped at 200 px for phone screen and about 42% of the screen for video, so the question shows without scrolling. I checked 375 px: no overflow.

For checking without models: a dev-only ?dev=room page shows the room beside the orb. You can drive it from the console with __room.heard('…') and __room.setAudioLevel(0.6, 'mic'). It's not in the production build.

Please try in Chrome (Phone screen, Light):

• Watch the orb glow as you talk and while Ananya speaks.
• Let an answer run past your target and check the timer turns amber, then red.
• Hide and show the captions.
• Then a video interview, to check the layout beside the avatar.

If it all looks right, I'll commit. Next is 4.3, the milestone: a full spoken interview end to end in Light, both video and phone. That's mainly your test in Chrome, and I'll fix whatever breaks.

The avatar is fixed and committed as 01da4e8, along with the interview room (193b1a3). I checked it in the browser for both Ananya and Aarav, on desktop and at phone width, but not yet with the models loaded in a real interview.

Why only the lower half showed: the package draws the avatar life-size, about 1.7 m tall with its feet at the floor. The camera I'd copied from the package README sits 0.15 m off the floor and 2.2 m back, so in our tall, narrow stage it could only see roughly from the knees to the waist.

The fix: a small HeadShot component inside the 3D canvas.

• Once the avatar is in the scene, it measures the model's bounding box.
• It points the camera at the head, shoulders and upper chest, with a little room above the head, and fits both the stage's height and its width.
• It reframes whenever the stage changes size: off-stage on setup, beside the interview, or on a phone's wider stage. So it works for any avatar, not just these two.

Checked: with a dev-only ?dev=avatar page (add &who=aarav for Aarav). It renders the avatar with loadModels={false}, so only the avatar file downloaded (about 4.5 MB each). Whisper, Kokoro and Gemma weren't loaded.

• Ananya: head and shoulders centred. The first version was framed down to the belt, so I tightened it.
• Aarav: head and shoulders.
• Phone width (343 × 320 stage): reframed correctly, nothing cut off.

Please reload a video interview in Chrome to confirm it looks right with everything running. The first frame may show the default view for a moment before it snaps to the head and shoulders, because the framing is measured once the model has loaded. If that blink bothers you, I can hide the stage until it's framed.

After that, it's 4.3, the full spoken interview in Light, video and phone.

Everything is ready for the full spoken interview (4.3). I've committed a dev-only session log on the report screen as 23086d3. It isn't in the production build.

The session log has every exchange: what the interviewer said, each stretch of your speech with its timing and speechMs, which follow-up angle was chosen, whether Gemma or a written line worded it, how each question ended (answered, skipped, silent, don't-know), and any notes. Open "Session log (dev only)" on the report, press Copy session log and paste it here; I'll work from that.

Run 1: Phone screen (Light → Phone screen → Ananya → Continue)

1. On setup: Behavioural, 3 questions, 2 min, Friendly, your name. Use Test microphone and Hear Ananya's voice, then Start interview.
2. Small talk: answer, then wait. It should move on after about 6 s of quiet, using your name in the greeting.
3. Question 1: answer with a deliberate 3 s pause in the middle. It should stay one answer under "What I heard", and the timer should keep running.
4. Watch the orb glow with your voice and with Ananya's.
5. Answer the follow-up, then press I'm done instead of waiting.
6. Question 2: say "Can you repeat that?", then "What do you mean?", then give a short "we did…" answer. The follow-up should ask what you did.
7. Question 3: say "I don't know" twice. You should get a nudge, then it moves on.
8. "Any questions for me?": ask one, then wait for the closing → See your report → copy the session log.

Run 2: Video interview (Practice again → Video → Aarav)

1. On setup: Full loop, Tough mood.
2. Check that Aarav is framed head and shoulders and lip-syncs, with a male voice.
3. Let one answer run past 2 minutes: the timer should turn amber, then red.
4. Press Pause, switch to another tab and back, then Resume.
5. Stay silent after one question: about 12 s for the nudge, about 25 s for it to move on.
6. Copy the session log at the end.

Worth noting as you go:

• Did anything cut you off mid-thought? Is 5 s of quiet too short or too long?
• Did any follow-up sound wrong, or repeat what you'd just said?
• How long from finishing an answer to hearing the follow-up?
• Anything that didn't respond, or looked off, on either screen.

Paste me the two session logs and anything you noticed, and I'll fix what breaks. The report itself (phase 5) is still a placeholder.

I fixed the off-target follow-up from your run and committed it as 4b734fc. All 92 checks pass, including your run's line.

The fix: if the rules ask for the outcome, Gemma's follow-up must actually ask about a result (turned out, impact, measured, changed, improved…). If they ask for ownership, it must ask what you did. Otherwise the written line for that angle is spoken. In your run, instead of "How did you handle those difficult feedback sessions?", you'd now hear "How did it turn out? Was there anything you could measure?". The recorded lines from the earlier model tests still pass at the same rate (Gemma 3 1B 8 of 12, Gemma 4 E2B 12 of 12), so good follow-ups aren't being thrown away.

Also from your log:

• Your 36 s answer arrived whole, in one piece, with nothing cut off.
• The wait before the follow-up was as designed: 5 s of quiet after your last words.
• Whisper heard "physical feedbacks" for "difficult feedbacks". That's the speech model's accuracy, not a bug in our code. If it keeps happening across runs, we can look at a larger Whisper or giving it the question as a hint.

One question, so I don't chase the wrong thing: the log ends right after that follow-up. It has no answer to it, only 1 of 3 questions, and it went straight to "done". Did you press End interview to send me the log? Or did it end, or stop responding, by itself? If it was by itself, tell me what you saw just before: the state label, and whether Ananya finished speaking the follow-up.

When you have time, Run 2 (video with Aarav, full loop, tough mood) would cover the parts this run didn't reach: pause and resume, silence, the timer past its target, and the closing.

Good, that means nothing is broken there: ending after the follow-up, with no answer and 1 of 3 questions, is exactly what End interview does.

So far your run confirms:

• Long answers: a 36 s answer arrives whole.
• Waiting: the 5 s long pause lets you finish before it moves on.
• Gemma follow-ups: they work in the real pipeline. The off-target one is now caught (4b734fc).

Still unconfirmed in a real run: the closing and "any questions for me?", the silence nudge and move-on, pause and resume (including a hidden tab), the timer past its target, and the video stage with Aarav (framing, lip sync, the male voice). Run 2 from my earlier list covers all of them in one go.

Two ways to continue:

1. You do Run 2 now and paste the log. I fix whatever comes up, then we close 4.3.
2. I start phase 5, the report, while you test when you have time. The report reads the same records the session log shows, and your log already has real data I can design against: answer text, speechMs and per-stretch timings.

Which do you prefer?

Step 1 is done: I committed the README, licence and ignore changes locally as 23f0355, and pushed nothing. There's one decision you need to make before step 2: pushing Entire's checkpoints to a public repo would publish this whole session's transcript, including your email address.

What I found:

• .gitignore already covered node_modules and dist. It was missing .env, .claude/settings.local.json and model-file patterns; I added them.
• Size: the largest file ever committed is package-lock.json at 0.16 MB. Nothing in the repo or its history is over 50 MB, and no model files were ever committed.
• Secrets in main's history: none. I scanned every commit's diff for OpenAI-, AWS-, GitHub-, Hugging Face- and Slack-style keys, private keys, bearer tokens and api_key / secret / password assignments: no matches. Your email isn't in any committed file. Commits are authored as 927tanmay <[REDACTED_EMAIL]>, which GitHub will show publicly.
• Entire. Checked with entire status, its git hooks, its own .entire/.gitignore and its security docs:
  • .entire/settings.json should be committed. The docs say Entire reads shared settings, such as redaction scanners, only from the committed file. Entire's own .entire/.gitignore already keeps metadata/, logs/, tmp/ and local settings out, so committing .entire/ adds only those two small files.
  • Checkpoints are separate from main. They're 16 git refs (refs/entire/checkpoints/*), about 115 MB before compression, with the largest file 9.6 MB. The pre-push hook pushes them with git push, because push_sessions defaults to true.
  • Every checkpoint is from this session only. Your earlier planning session (398d8298…, the one with personal notes) is in none of them; it sits only in the ignored .entire/metadata/.

What I changed and committed:

• .gitignore: added .env, .env.* (keeping .env.example), .claude/settings.local.json, .entire/settings.local.json, model files (*.onnx, *.onnx_data, *.gguf, *.safetensors, *.glb, models/) and .measure/.
• README.md:
  • what it is and that everything runs in the browser;
  • a demo-link placeholder;
  • how to run it locally, with the first-visit download sizes;
  • the model table with licences;
  • how it works, with a plain note that you maintain react-ai-voice-avatar and the app is new. I marked the report as "being built" so it doesn't promise anything unfinished.
• LICENSE: MIT, "Copyright (c) 2026 Tanmay".
• Also committed: .entire/settings.json and .entire/.gitignore, plus .claude/settings.json (only the Claude Code hooks Entire installed, which do nothing if entire isn't installed) and .claude/launch.json (dev-server config).

The decision for step 2. Each checkpoint holds this session's full transcript: every message, all tool output, about 78 screenshots, your home path, and your email address, once in each checkpoint. The email comes from context Claude Code attaches to the session, not from anything you typed. Entire redacts secrets automatically, but its email redaction is an opt-in layer that's off by default, and it was off when these were written. Its docs say plainly: "If your repository is public, so are they." The two "AKIA…" key-like strings are false positives inside screenshot data.

Your options:

1. Push as planned: the checkpoints and your email go public with the repo. That's simplest, and the Entire prize post can link straight to them.
2. Keep checkpoints out of the public repo: entire configure --checkpoint-remote github:927tanmay/interview-room-checkpoints sends them to a separate repo you can keep private. Or entire configure --skip-push-sessions keeps them local only.
3. Turn on Entire's PII redaction for future checkpoints, then choose 1 or 2 for the existing 16. The docs don't say whether enabling it re-redacts checkpoints that already exist, so I'd assume it doesn't.

Entire's own help lists configure as a command for you to run, not me, so I haven't changed its settings. Tell me which option you want. If you pick 2 or 3, run the entire configure command and say "go", and I'll do step 2 accordingly.

The email is out of all 16 existing checkpoints. Entire still reads every one of them, and new checkpoints now come out clean on their own. Nothing is pushed yet.

Backup: a mirror clone at /Users/tanmay/Documents/interview-room-backup-2026-10-04.git (83 MB). It has all 17 refs, matching the repo before the rewrite, and still contains the unredacted checkpoints, so keep it local.

How Entire stores checkpoints, and why I didn't use git-filter-repo:

• Each checkpoint is its own tiny history of one or two commits under refs/entire/checkpoints/<xx>/<id>, with no link to main. Zero main commits are reachable from them, so rewriting them can't affect main.
• Each checkpoint stores content_hash.txt = the SHA-256 of its full.jsonl. filter-repo --replace-text would change the transcript but leave that hash stale, and every checkpoint would fail Entire's integrity check.
• So I didn't need to install it. A small script using plain git plumbing replaced the address with [REDACTED_EMAIL], recomputed each content_hash.txt, and recreated each commit with the same author, dates, message and parent chain. It moved only the refs/entire/* refs, and only after checking each old hash matched its old transcript. Result: 16 refs moved, 31 commits and 33 files rewritten, 31 hashes recomputed.

Verified afterwards:

• Your email: 0 occurrences across all 31 checkpoint commits, every file, with 74 [REDACTED_EMAIL] markers in their place.
• Integrity: 0 hash mismatches, and 0 invalid JSON lines in the transcripts.
• IDs: ref names unchanged. All 16 Entire-Checkpoint trailers on main have a matching ref and vice versa, and each ref name matches the checkpoint_id in its metadata.
• main: untouched, still 23f0355 before and after the rewrite.
• Entire reads them:
  • entire checkpoint list shows all 16, linked to the right commits;
  • explain --short works on the oldest (50ecef9, "Initialise project") and the newest;
  • --raw-transcript serves 9.6 MB with 0 copies of the email.

New checkpoints: your redaction setting is valid, and I committed it as 8d57839. That commit's checkpoint (…133MN) has 0 copies of your email and 46 markers, so Entire is now redacting as it writes. That includes the copies my own scan commands had put into this session's transcript; since then I've only written the address in pieces.

The 39 screenshots (stored twice each in the transcript, which was the 78 I counted before). All are of the app on localhost: no browser bar, no other tabs, no desktop, no names.

• Home page (10): early placeholder versions, the device check (ready, Heavy unavailable without shader-f16, no WebGPU), and the download table on desktop and phone.
• Setup (13): the video/phone choice, with Ananya and Aarav added later; model progress (downloading, ready); the options; the mic panel.
• Interview screens (9): the early placeholders, the phone orb, the answer timer at 0:24 and at 0:21 / 0:15 in red, and phone-width layouts.
• Avatars (5): Ananya and Aarav framing previews: 2 loading, 3 loaded.
• Blank (3): gradient-only frames caught mid-reload.
• Dev panel (1): the Gemma test panel.

Nothing private in the screenshots. The transcript text has a few things you may want to know will be public with the checkpoints:

• your home path (/Users/tanmay/…) and machine details: M4, 16 GB, 43 GB free disk;
• the answer you spoke in your test run, about team members underperforming and receiving feedback;
• your intro message saying the app is for a friend who's job hunting, and that their laptop is an M2 Pro;
• your git identity [REDACTED_EMAIL], which is on every commit anyway.

The old, unredacted checkpoint objects still sit unreferenced in the local .git until garbage collection. git push only sends referenced objects, so they won't go to GitHub.

Stopping here. When you say go, step 2 creates the public repo 927tanmay/interview-room and pushes main, with Entire's pre-push hook pushing the 17 checkpoints.

The repo is public at https://github.com/927tanmay/interview-room, and main plus all the checkpoints are on GitHub.

• main: pushed to 8d57839 and set to track origin/main. It's the default branch, and the repo is public with a short description.
• Checkpoints: Entire's pre-push hook ran and reported "Pushing 17 checkpoint ref(s) to origin… done". I checked GitHub directly: all 17 refs/entire/checkpoints/* are there, with exactly the same SHAs as my local redacted copies. Identical SHAs mean identical contents, so what's on GitHub is the version with your email removed.
• Nothing else went up: GitHub holds only main and the checkpoint refs. The local backup, the old unredacted objects and .entire/metadata/ (including your earlier planning session) all stayed local.
• Entire: with origin set, Entire now finds the repo by itself; entire checkpoint list shows 17 checkpoints on main.

From here, every git push sends new checkpoints along with the code, and they're redacted as they're written.

Stopping here. Next is step 3, the render.yaml: a static site built with npm ci && npm run build and published from dist, with the same cross-origin isolation headers as the dev server, plus click-by-click steps for the Render dashboard. One note for it: the app has no URL routes (screens switch in state), so an SPA rewrite isn't strictly needed. I'd still add one, so a typo'd or refreshed path loads the app instead of a 404.

The Render setup is ready and committed locally as 6d0d49b. Render reads render.yaml from GitHub, so I need to push before you connect it. That's one commit on top of what's already there, and Entire will push its checkpoint along with it. Can I push?

What's in it:

• render.yaml:
  • a free static site;
  • build command npm ci && npm run build, published from ./dist;
  • auto-deploys on every commit to main.
• Node version: pinned to 24.9.0, what you use locally, in two places. One is NODE_VERSION in render.yaml, which Render checks first. The other is a .node-version file, which nvm, fnm and similar tools also read.
• Headers on every path: Cross-Origin-Opener-Policy: same-origin and Cross-Origin-Embedder-Policy: require-corp, the same values as the Vite dev and preview servers.
• Two additions you didn't ask for:
  • Caching: hashed /assets/* files are cached for a year, and the page itself is always rechecked, so a new deploy shows up straight away.
  • Unknown paths: they rewrite to index.html. The app has no URL routes, so this only turns typos and old links into the app instead of a 404. Render never applies it when a real file exists at the path.

No model files in dist. A fresh clone built with Render's exact command gives 11 files: no .onnx, .onnx_data, .glb, .safetensors or .gguf, and none of the dev panels. The models download from Hugging Face at runtime. The largest file is a 26.9 MB ONNX Runtime binary that the bundler copies in. Production never uses it, because transformers.js always loads the runtime from jsDelivr, so visitors never download it either.

Would the headers block anything cross-origin? No. I tested every host with an Origin header, following redirects as a browser would:

The github.com, web.dev, react.dev and similar addresses in the bundle are links inside library comments and error messages, not things the app loads.

What to click in Render (after I've pushed):

1. Go to dashboard.render.com → New + (top right) → Blueprint.
2. If GitHub isn't connected: click Connect GitHub, authorise Render, and when asked which repos it can access, choose Only select repositories → interview-room.
3. Pick 927tanmay/interview-room from the list → Connect.
4. Render reads render.yaml and shows one service: interview-room (static site, free). Leave the branch as main, give the Blueprint a name if asked (for example interview-room) → Deploy Blueprint (labelled Apply on some screens).
5. Wait for the first build, about 1–2 minutes; you can watch the log on the service page. The site gets a URL like https://interview-room.onrender.com, with a suffix if the name is taken.
6. Send me the URL, and I'll do step 4: check the headers, crossOriginIsolated, model downloads under the headers, the mic over https, and a full interview. I'll also put the URL in the README's demo link.

No API keys are needed anywhere, and free static sites on Render stay up without sleeping.

Pushed: main on GitHub is now at 6d0d49b ("Add a Render Blueprint for the static site").

• On GitHub: render.yaml (1,798 bytes) and .node-version are both in the repo, so Render can read the Blueprint.
• Entire: the pre-push hook sent this commit's checkpoint (…GAHJ). It's on GitHub with the same SHA as my local copy, and it contains no copies of your email.

You can connect it in Render now:

1. dashboard.render.com → New + → Blueprint.
2. Connect GitHub if asked: authorise Render, choose Only select repositories → interview-room.
3. Select 927tanmay/interview-room → Connect.
4. Check that it shows the interview-room static site on the free plan, branch main → Deploy Blueprint (or Apply).
5. Wait about 1–2 minutes for the build, then send me the URL.

With the URL, I'll do step 4: headers, crossOriginIsolated, models downloading from Hugging Face under the headers, the mic over https, a full interview, and anything that behaves differently from local.

The fix is pushed: I removed only the plan: free line from render.yaml and pushed it as 89ae844, with Entire's checkpoint sent alongside. It isn't up yet.

https://interview-room.onrender.com currently returns Render's own 404, so no service is answering at that name. Most likely Render hasn't created the service yet, because the first Blueprint was rejected. In the Render dashboard, open the Blueprint and press Retry, Sync or Apply (or create the Blueprint again from the repo) so it reads the fixed file.

I'm checking that address every 20 seconds in the background, for up to 30 minutes, and I'll tell you when it answers with our headers. If Render gave the site a different URL, for example with a suffix because the name was taken, send it to me and I'll check that one instead.

I've stopped the background check, and nothing else is running.

Good to hear it's deployed. When you're ready for step 4, send me the site's URL and I'll check it against local: the headers, crossOriginIsolated, model downloads from Hugging Face under those headers, the mic over https, and a full interview. I'll also put the URL into the README's demo link.

The site at https://interview-room-iooj.onrender.com works like local everywhere I could test. What I couldn't test from here is the mic and a full spoken interview; that needs you in Chrome.

Differences from local:

• Unknown paths aren't no-cache. They get Render's default max-age=0, s-maxage=300 instead of the no-cache I set for / and /index.html. That only affects typo'd URLs, and browsers still revalidate, so it's harmless.
• Nothing else differed. The build on Render is the same commit as local; the asset names match exactly.

Not tested here:

• Mic over https: Claude's browser pane has the microphone blocked by its own policy (it reports "denied"). The site has everything a mic needs (https, a secure context, getUserMedia), but please confirm in your Chrome: allow the mic, use Test microphone, check that "Heard: …" appears.
• A full interview on the live site: it needs speech, so please run one there. A first visit downloads about 1.6 GB for Light, and a reload should then show "Loading from this device". If anything differs from local, the dev-only session log won't exist on the live site, so tell me what you saw.

README: the demo link now points at the live URL, with "Chrome or Edge on a laptop or desktop". I committed it locally as 599b05e and haven't pushed. Pushing triggers a Render redeploy and sends one more checkpoint, which will be redacted. Should I push it?

I checked both against the code. Here's what's there, and how I'd split phase 1. I haven't changed anything yet.

The question bank (src/interview/bank.ts, 56 questions)

• No short points with tags. Each question has a prose sampleAnswer ("Sets the scene in a sentence…, says what they owned, walks through the concrete steps…, ends with the result…").
• 2–3 keyPoints per question, each a label plus phrases for the code to match. The labels read like rough points ("the outcome", "their own part", "how they narrowed the problem down"), but there's no tag, and there are only 2–3.
• The engine uses those keyPoints to pick the "missing point" follow-up angle, so I'd keep them as they are and add a new field: 3–5 points, each { tag, text }, written from the prose plus the labels.
• Tags: your examples (result, own role, example, trade-off, edge case) fit behavioural questions. Technical and HR questions need a few more. I'd propose one shared set of about 8: situation, own-role, action, result, example, trade-off, edge-case, concept, plus motivation for HR. Then "you left out the result in 3 of 4 stories" works across rounds.

The engine snapshot (src/interview/engine.ts)

• Per question: the bank question, how it ended (answered, skipped, silent, don't-know), start and end times, and the exchanges: question, follow-up, probe, clarification.
• Per exchange: what the interviewer said, the follow-up angle, whether Gemma worded it, and the answer as parts, one per stretch of speech, each { text, speechMs, at }.
• Also: notes (for example, Gemma failing), small talk, and the candidate's questions.
• What's missing for your measurements:
  • Time to first word: the engine is told when the interviewer's voice ends (interviewerFinished), but doesn't store when.
  • Pauses over 3 s: at is when the transcript arrived, which is about 1.5 s after the stretch ended, not when the speech started or stopped. I'd record the real start (from the "candidate started talking" signal) and end of each stretch. The voice detector only splits on pauses longer than 1.4 s, so a pause over 3 s always falls between stretches, and those times are enough.
  • Target time: your target (answerMinutes) and track live in the app's settings, not the snapshot. The report needs them stored with it.

How I'd split phase 1 (a report after each, as usual):

1. Points and tags. Draft the tag set, write points for about 4 questions (a behavioural, a technical, an HR and one more) and show you before doing all 56. System design is parked, so I'd skip those 10 for now unless you want them.
2. Timing in the engine. Record when each question finishes being spoken, and when each stretch starts and ends. Add these to the engine's no-mic tests.
3. Measurements as plain functions, tested in the Node script with the engine's:
   • time per answer against your target, and where the target was crossed (for the shading);
   • words per minute from speaking time, against the 120–160 band;
   • time to first word, and pauses over 3 s;
   • the fillers Whisper keeps ("you know", "I mean", "basically", "kind of", "like" with a comma), with their positions for highlighting;
   • "I" against "we", and numbers mentioned;
   • skipped or empty answers marked skipped, not measured.
4. Report data, fake interview, persistence.
   • one saved report record: settings, answers, measurements, your marks;
   • a dev page with a fake interview (mixed answers: strong, "we"-heavy, over time, skipped);
   • saving to IndexedDB, so a reload brings the report and marks back.
5. The self-review screen:
   • one answer at a time: question, your answer, "How did that one feel?" (good / okay / rough);
   • then the points beside your answer: covered / partly / missed;
   • keyboard shortcuts, a progress bar, and "Skip to the numbers".
6. Focus rules as plain tested functions:
   • up to three things to work on: the most-missed tag, answers that felt good but were mostly marked missed, the one furthest over target;
   • each says where it came from and links to that answer;
   • the gentle disagreements: "result" marked covered with no numbers, or "own role" covered with far more "we" than "I".
7. The report page:
   • the focus list;
   • a card per answer: the quote with fillers highlighted and the over-target part shaded, the follow-up and your reply, the numbers, your marks;
   • plain SVG charts with the numbers written on them;
   • a "Practice this one again" button per answer;
   • the how-it-was-measured footer (Whisper drops um/uh, can mishear technical terms, nothing left the device);
   • print-to-PDF styles.
8. One real Light interview end to end. I can't speak into a microphone from here, and Claude's browser pane blocks it anyway. I can run the real app with real Gemma and feed it transcripts through a dev hook, which tests everything after Whisper. The real spoken run would need you, or that hook run counts as the check. Which do you prefer?

Things to settle before or during these steps:

• "Practice this one again": the voice engine unloads when the report opens. So I'd send you back to setup with that one question preselected. The models reload from disk, which took about 4 s on your M4.
• Spelling: your brief says "practise this one again". Earlier you asked for "practice", so I'll use "Practice" unless you say otherwise.
• Heavy as "coming soon": I'll add a simple switch on the home page now, so on Monday at 8 am IST it's a one-line change if Heavy isn't ready.
• README push: the demo-link commit (599b05e) is still local, waiting for your go to push.

If that split works for you, I'll start with step 1: the tag set and 4 sample questions for you to review.

I've drafted the tag set and points for 4 sample questions in src/interview/bank.ts, as a new points field. It type-checks. The existing keyPoints the engine uses for follow-ups are untouched. Nothing is committed.

The tags, 11 of them, with how they'll show on screen:

That's more than your five examples. Technical and HR questions don't fit "result" or "own role", so they need their own tags. The report groups your marks by tag across answers.

The four sample questions:

b-improved: "Tell me about a time you improved something that was not working well."

• Situation: What was not working, and how you knew
• Your role: The part you personally owned
• What you did: What you changed, and why that option
• Result: A before-and-after result, ideally a number

b-feedback: "Tell me about a time you received difficult feedback." (the question from your real run)

• Situation: What the feedback was, and who gave it
• What you did: How you responded: asked questions, listened, did not argue
• Lesson: One concrete thing you changed afterwards
• Result: How you knew the change worked

fe-useeffect: "Can you explain what the useEffect hook does in React and when you would use it?"

• Core idea: Runs side effects after React renders
• Example: A real use: fetching data, a subscription, a timer
• Core idea: The dependency array decides when it runs again
• Edge case: Cleanup on unmount or before the next run
• Trade-off: When you do not need an effect, such as derived values

h-leaving: "Why do you want to leave your current job?"

• Motivation: What you are moving towards: scope, learning, a kind of product
• Example: Something specific this role offers that you want
• Framing: Something fair or good about your current job
• Framing: No complaints about pay or people

How I wrote them:

• Checkable: each point names one thing you can look for in your own answer and mark covered, partly or missed.
• Short: 5–12 words each, addressed to you.
• From the bank: taken from each question's sample answer and key points, so nothing new is invented.
• Count: 4 points for behavioural and HR questions, up to 5 for technical, where there's more to cover.
• Repeated tags: a tag can appear twice in one question (two "Core idea" points, two "Framing" points). The report would count those separately.

Questions for you:

1. Is the tag set right, or would you merge any? For example, lesson into result, or drop framing and treat HR differently.
2. Is this length and tone right, or would you rather have shorter points, or questions such as "Did you give a number?"
3. All 46 non-system-design questions, with system design skipped while it's parked?

Once you've answered, I'll write the rest and run a check: 3–5 points each, valid tags, no duplicate wording.

Step 1 is done. All 46 questions outside system design now have strong-answer points in src/interview/bank.ts: 206 points in total. The 10 system design questions are left without them while that part is parked. Nothing is committed.

Check results: the type check passes. A check script found no problems: every question has 3–5 points, every tag is one of the 11, no point is over 12 words, and no two points repeat the same wording.

How the points are spread across tags:

Your role is rare, on purpose. It only appears where the question itself asks about ownership (improved, pressure, mistake, proud). Elsewhere, ownership shows up in the measured "I" against "we" numbers rather than as a point to mark.

Some points have more than one thing in them, for example "Contrast and alt text". You'd mark these "partly" if you mention only one. I kept them together so the lists stay at 3–5 points.

A few to look at if you want to spot-check the tone:

• b-conflict: ends on "The working relationship afterwards, not being right".
• be-incident: "Roll back or flag off before digging in".
• ml-attention: includes the quadratic cost as an edge case.

The script that wrote the points and the check script are in my scratchpad, not the repo. Running the check made npx fetch tsx into npm's cache, not the project. I should have asked first, and I'll ask before doing that again.

Step 2 is next: record timings in the engine (when the interviewer finishes asking, and when each stretch of your speech starts and ends). Want me to commit step 1 first?

I committed step 1 as d1e0d5e ("Add strong-answer points and tags to the question bank"), without a co-authored-by line, and the working tree is clean.

Nothing is pushed. Two commits are only on this machine: this one and the README demo link (599b05e). I'll ask before pushing.

Step 2 is next: recording when the interviewer finishes asking and when each stretch of your speech starts and ends. Shall I go ahead?

Step 2 is done. The engine now records when you actually start and stop each stretch of speech, and when the interviewer finishes asking. Type check, lint and the production build pass, and all 101 engine checks pass (9 of them new). It isn't committed, and I haven't checked it with a real microphone yet.

Where the times come from

• When you stop talking: the package fires onInferenceStart the moment the voice detector closes a stretch of speech, before Whisper runs. The detector has by then waited 1.4 s of silence (its default, which the app doesn't change), so the end time is that moment minus 1.4 s.
• When you start: the end time minus speechMs. speechMs is the package's own figure for how long you spoke, counted from the detector's frames, so the start is about as accurate as the end.
• When the transcript arrives: still kept separately as at, so nothing that used it before changes.
• When the interviewer finished asking: stored as askedEndedAt on each exchange, from the existing "interviewer stopped speaking" signal. Each exchange also stores askedAt, when it was asked.

Rules for time to first word

• The clock starts when the question finishes, and restarts after a repeat or rephrase you asked for, or a re-ask after a pause.
• A silence nudge ("Take your time…") doesn't restart it. Otherwise the nudge would hide the hesitation the number is meant to show.
• An end time is used once only. If the stretch turns out to be "repeat that" or garbled, it isn't carried over to your next answer.

Two limits for step 3

• If you talk over the interviewer, your start can come before askedEndedAt. The measurement will show that as "started before the question ended", not as a negative time.
• If the detector's signal is missing (typed input, or the dev page's fake interview), the stretch has no times. It will be shown as "not measured" rather than guessed.

Changed files: engine.ts, session.ts, and the voice wiring: voiceEvents.ts, VoiceHost.tsx, PhoneVoice.tsx, VideoVoice.tsx.

One assumption to confirm. I read the package's built code to find which callback fires at speech end, and onInferenceStart has no description in the package's type files. If you change the package later, it's worth giving it a clear name and description, such as onSpeechEnd. I haven't touched the package.

Shall I commit step 2 and move on to step 3, the measurement functions and their tests?

Step 3 is done. The measurement functions are in src/report/measure.ts: plain code, no Gemma, instant. All 130 checks pass (29 of them new). Type check and lint pass too. Not committed.

What it measures

Missing times aren't guessed. If the voice detector's times are missing (typed input, or a missed signal), timing, pace and over-target come back as "not measured" (null).

Choices to check

1. I added "sort of". It works like "kind of" and wasn't on your list, so it's easy to remove.
2. Pronoun and number lists. "us" and "our" count as "we"; "half", "twice" and "dozen" count as numbers. I left out "double", because "double-check" would be counted wrongly.
3. Follow-ups. Replies to follow-ups count towards the interview totals (fillers, words, "I" and "we"), but not towards the answer-length target, which applies to main answers only.

Shall I commit and move on to step 4: the report data, the dev page with a fake interview, and saving to IndexedDB?

Step 4 is done. When an interview ends, the app now builds a report from what the engine recorded and saves it on the device in IndexedDB. A dev page runs a fake interview through the real engine. Type check and build pass, and the fake code isn't in the production build. Lint gives one warning, in the dev page only (setting state from its loading effect); I left it. Not committed.

What's in a report (src/report/report.ts)

• What it holds: the engine's records as they were, copied when the interview ends. Each record includes the full question with its points, so an old report reads the same after the bank changes. It also holds the settings, light or heavy, phone or video, the hello and your questions at the end, and any notes such as Gemma failing.
• Your marks: saved in the report. For each answer, how it felt (good / okay / rough), then covered / partly / missed per point. There's also a review state: not started, in progress, done, or skipped (went straight to the numbers).
• What isn't saved: the measured numbers. They're worked out from the records each time, which is instant.
• What the self-review covers: only answered questions that have points. Skipped, silent and empty ones show in the report as such.

Saving (src/report/store.ts)

• Saved in IndexedDB.
• Every report is also kept in memory, so the report screen opens immediately without waiting for the save.
• In a private window or where storage is blocked, it still works until the tab closes, and the save reports that it wasn't stored.

Wiring

• Either way the interview ends ("See your report" or "End interview"), the report is made, saved and opened.
• The interview's voice listeners are then detached.
• The report screen loads by id, so it survives a reload.

Fake interview (?dev=report)

• It runs the real engine with a fake clock and the same signals the voice sends. Covered:
  • a 73-second answer against a 1-minute target, mostly "we", with fillers and a 4.2 s pause;
  • a follow-up reply;
  • a technical answer;
  • a skipped question;
  • an answer that starts over the end of the question.
• Checked in the browser: every number came out as designed (12.9 s over target, shaded from "in around 2 seconds…"; "we" 11 to "I" 2; 122 wpm; first word 2.6 s). After a reload, the same report came back from IndexedDB.
• What you see for now: a placeholder, plus dev-only "Session log" and "Measured" panels you can copy. The real page comes in steps 5 and 7.

Not tested: the save at the end of a real spoken interview, which needs the microphone. That's covered by step 8's real Light run.

Shall I commit and start step 5, the self-review screens?

Step 5 is done: the self-review now opens when an interview ends, before the report. Type check, lint and build pass, and I tested it in the browser on the fake interview. I committed step 4 first (a762a5e), as you'd said to go ahead. Step 5 is not committed.

How it works (Review.tsx)

1. How it felt. The question, your answer in your own words, and the follow-up with your reply (points are often covered there, such as cleanup in the useEffect follow-up). Then "How did that one feel?": Good / Okay / Rough.
2. The points. Your answer on the left, "What a strong answer usually covers" on the right. Each point shows its tag (Situation, Your role…) and Covered / Partly / Missed. The line under the heading says "It's your call; nothing here is scored." On a phone they stack, with a shorter answer box so the points stay close.

• Progress: dots and "Answer 2 of 3 · the points".
• Navigation: Back, Next answer, and "See the report" on the last one. "Felt: Okay. Change" lets you go back and change the feel.
• Skip to the numbers: on every step. It keeps any marks you've made.
• Saving: every mark is saved to IndexedDB as you make it. Coming back (even after a reload) resumes at the first unfinished answer.
• After the review: the report screen offers "Change your marks", or "Look back at your answers" if you skipped.
• What's reviewed: only answered questions with points. Skipped and silent ones aren't reviewed.

Keyboard

• 1 / 2 / 3 picks the feel.
• C / P / M marks the highlighted point and moves on to the next unmarked one.
• ↑ ↓ (or J / K) moves the highlight.
• Enter goes to the next answer; Backspace goes back.
• The shortcuts only work while focus is inside the review, so they don't clash with screen readers. Each one has a button or radio that does the same. Focus moves to each step's heading.
• The key hints are shown on screen.

What I tested in the browser

• The whole fake interview by keyboard only, about 25 key presses for 3 answers.
• Backspace keeps the earlier choice.
• A reload in the middle resumes at answer 2.
• Finishing saves all 13 marks with the state "done".
• Skip saves the state "skipped" and keeps the marks.
• At phone width (375 px) there's no sideways scrolling.

Two choices to confirm

• Unmarked points are allowed. You can press Next with some points unmarked; nothing forces you to mark everything. The report will treat unmarked points as "not marked", not as missed.
• The follow-up counts as part of the answer. The reply is shown with the answer, so a point covered in the follow-up can be marked covered.

Shall I commit and go on to step 6, the focus rules and gentle disagreements?

Step 6 is done. The focus rules and gentle disagreements are plain functions in src/report/focus.ts, with number formatting in format.ts. All 150 checks pass (20 of them new). Type check, lint and build pass. I committed step 5 first (b4762af); step 6 is not committed.

Things to work on: up to 3, one per rule, in this order

Each item lists the answers it's about, so step 7 can link to their cards. If you skip the review, only the measured rules can fire. Unmarked points don't count as missed, and one "partly" doesn't make a point "missed".

Gentle disagreements

• Result marked covered, but no number heard: "…If you gave one, Whisper may have missed it; if not, a before-and-after figure makes a result easier to believe." A number in the follow-up reply counts.
• Your role marked covered, but "we" at least twice as often as "I" (and 4 or more times): "…you said 'we' 5 times and 'I' 1 time. It is worth a second look…"

Changed after trying it on the fake interview you marked

• Tie-break: "example" (missed in 1 of 2) was beating "the result" (missed in 1 of 1). Ties now go to the higher share missed.
• Over-target threshold: a fixed 15 s missed the 13 s overrun on a 1-minute answer. It's now 15% of the target, at least 10 s.
• Single answers: they now read "in the one answer where it came up".
• Fillers minimum: raised from 4 to 5, so a short interview with a few fillers doesn't get an item for it.
• Current result: the fake interview now gives "End with the result", "Keep answers nearer the target", and "Fewer filler phrases".

The focus items and disagreements also show in the dev "Measured" panel.

Shall I commit and go on to step 7, the report page itself?

I've built the report page and checked it in the browser on the fake interview. Two things aren't checked yet: the PDF printout and the "Practice this one again" flow end to end. All 150 checks, type check, lint and build pass. The word "score" appears only in two code comments saying there are none. Not committed.

What's on the page, top to bottom

1. Summary line: date, how many questions and how many you answered, phone or video, Light or Heavy.
2. Things to work on: up to 3, each with where it came from ("From your own marks." / "Measured from your first word to your last…") and links to the questions it's about. If nothing stands out, it says so; after a skipped review, it suggests going back to mark your answers.
3. Worth a second look: the gentle disagreements, each linking to its question.
4. The numbers: four plain SVG charts, each bar labelled with its value and a text summary for screen readers.
   • Answer length, with a dashed target line and the part past the target striped.
   • Pace, with the 120–160 band shaded.
   • Time to first word ("before it ended" when you talked over the question).
   • Filler phrases.
   • Under the charts: a line with total words, "I" and "we" counts, and pauses.
5. Your answers: one card per question.
   • Quote: your own words with fillers underlined, numbers in bold, "pause 4.2 s" marked where you picked up again, and a "past your target from here" marker with the rest faded and striped.
   • Follow-up: the interviewer's line and your reply, marked the same way.
   • Measured: length against target, pace, first word, pauses, fillers, "I" and "we", numbers.
   • Your marks: how it felt, and each point as ✓ Covered / ~ Partly / ✗ Missed / Not marked (words, not just colour).
   • Practice this one again.
   • Skipped, silent or empty questions: a card saying so, "not measured".
6. How these were measured: each number explained. The footer also says um/uh aren't counted, that the marks are yours and the app doesn't judge, that Whisper base can mishear technical terms, and that nothing left the device.
7. Actions: "Change your marks" (or "Look back at your answers"), Home, Save as PDF, Practice again.

Practice this one again

• It goes back to setup titled "Practice one question again", showing the question. Track, level, round and count are hidden; answer length and manner stay.
• It asks just that question, with a follow-up, then makes a new report.
• It uses the question as it was asked then, from the report. Because the voice models are unloaded on the report screen, you pick phone or video again; the models load from the device cache.

Print / Save as PDF: dark text on white, no glass or blur, buttons and dev panels hidden, and cards and charts don't split across pages.

Fixed along the way

• The chart text was too small at first (the drawing scaled down to about 8 px). It's now 13–14 px on desktop and phone.
• I briefly ran Prettier on the setup screen, which reformatted the whole file. The project doesn't use it, so I restored the file and redid my edit by hand.

Checked in the browser: desktop and 375 px phone width (no sideways scrolling).

Not checked yet

• The PDF printout. I couldn't preview print here. Could you try "Save as PDF" in Chrome on ?dev=report?
• "Practice this one again" end to end. It needs the models, so the real Light run in step 8 will cover it. On the dev page the button only shows an alert.

Shall I commit, and then do step 8, the real Light interview? For step 8, do you want to run it spoken, or should I drive real Gemma through a dev hook?

I committed the report page as c293b22. Phase 1 is now 7 local commits that aren't pushed. Here's the plan for step 8.

Step 8: one real Light interview, end to end

Goal: check that the timings, report and review hold up with a real microphone, real Whisper and real Gemma. Then fix anything that's off and stop; phase 1 ends there.

Who runs it: I recommend you run it, spoken, in Chrome. My browser pane can't use the microphone, and earlier it lost the downloaded models because of its storage quota. Driving Gemma through a dev hook would skip the parts most likely to break: the voice detector's timing signal, Whisper's transcripts and the moment a question ends.

Where: your local dev server, localhost:5173 on main, in Chrome, Light mode, with the models already on your device. The new code isn't on Render until we push, and I'll ask before that.

Settings: phone screen (lighter), full loop, frontend, junior, target 1 min (so going over is easy to trigger), friendly.

Things to do during the run, so each feature gets used:

1. Answer small talk normally.
2. Question 1: answer for longer than a minute. Pause once for about 5 seconds in the middle, use a couple of fillers ("basically", "you know"), and mention one number.
3. Reply to the follow-up.
4. Question 2: say "can you repeat the question?" first, then answer briefly.
5. Question 3: press Skip.
6. Question 4: start talking just before the interviewer finishes the question.
7. Finish normally ("See your report").
8. Review: use the keyboard (1/2/3, C/P/M, Enter). Reload once in the middle.
9. Report:
   • check the numbers feel right; a phone stopwatch on one answer helps;
   • press Save as PDF and look at the preview;
   • press "Practice this one again" on one answer and run it.

What to send me: at the bottom of the report, open the dev panels "Session log" and "Measured", copy both, and paste them here. Add anything that felt off, and any console errors.

What I'll check in the logs

• The timing signal works: every stretch has from/to times, and every question has askedEnded. This is the biggest risk: onInferenceStart has no description in the package's type files, so I worked out from its built code that it marks the end of speech. If it doesn't fire, timing shows as "not measured", and I'll fix it.
• Times add up: the detector's times (from/to) line up with when transcripts arrived (t), about 1.4 s for the detector's wait plus Whisper's time.
• Plausible numbers: pace about 110–180 wpm; the ~5 s pause shows as a long pause; question 4 shows "talked over"; the repeat restarted the time to first word.
• Fillers and numbers: Whisper's actual spelling of fillers and numbers matches the patterns (for example, does it write "9" or "nine"?).
• Gemma's follow-ups still pass the guard.
• The report: saved, reloads, and the practice run makes a second report.

Then: I fix what's off with a test for each fix and commit, and phase 1 is done. I won't start phase 2 (the embedding helper) until you say go.

Still open, separate from step 8

• Pushing: 7 phase-1 commits plus the README demo link are only on this machine. Pushing redeploys Render. Tell me when.
• Heavy: if Heavy isn't working by Mon 8 am IST, I'll switch it to "coming soon" on the home page. It's a small change I can do any time you say.

Ready when you've done the run. Paste the two logs and any notes here.

Thanks. Most of it worked, and the run turned up four bugs and one timing question. You pasted the Session log only (no Measured panel), but I can work out the measured numbers from it.

What worked

• The timing signal fires. Every stretch of speech has start and end times, and every question has the time the interviewer finished asking. So onInferenceStart does mark the end of speech; that was the biggest risk.
• Times add up. Transcripts arrived 1.7–2.9 s after you stopped talking (the detector's 1.4 s wait plus Whisper), which is about right.
• Pace looks plausible: about 157, 112, 127 and 141 words a minute.
• The flow held together. Skip, the follow-ups, ending mid-question (h-leaving is correctly "empty, not measured"), the review (all marks saved, state "done") and the saved report all worked.

Problems found

1. Saying "skip" doesn't skip.

• What happened: "Well, can you please skip this question?" was taken as your answer. Gemma then asked a follow-up about it ("Can you walk me through the process?"), and you had to press Skip.
• Cause: there's no spoken skip command.
• Fix: a skip intent for "skip this question", "can we skip", "next question" and "move on", checked only on short stretches like the other commands.

2. "Sorry, I don't know about that." wasn't recognised as "I don't know".

• What happened: it was stored as your follow-up reply.
• Cause: the pattern only allows "um", "uh" or "so" before "I don't know".
• Fix: allow "sorry", "honestly" and "actually" before it too.

3. Gemma's follow-ups drifted off the gap the rules picked. Both were the "missing point" kind of follow-up:

• The URL question: the rules wanted a missing point, but Gemma asked about DNS again, which you'd already covered.
• The useEffect question: it asked "Do you see how it helps with state management?". That's off the missing point (likely cleanup) and hints at a wrong answer.
• Fix: the guard already checks the outcome and ownership follow-ups for the right words. Do the same here: Gemma's line must mention the missing point (for example, "cleanup"), otherwise it falls back to the written follow-up ("Could you say a bit about cleanup?").

4. The measurements missed real cases.

• "like" with the comma before it: Whisper wrote "it first goes to the, like we write it…", with the comma before "like". Several fillers went uncounted.
  • Fix: also count ", like" when followed by I, we, you, it, they, so or suppose, and "Like I…" at the start of a sentence.
  • Trade-off: "Like I said" would count as a filler. "things, like React" still wouldn't.
• "one or two members" counted as a number. That stopped the "result marked covered, but no number heard" note on the feedback answer. You marked everything covered there, and its only number was this vague one.
  • Fix: ignore vague ranges like "one or two" and "two or three".

Timing question: is time to first word too short?

What the log shows:

• Most answers start 0.5–1.0 s after the question ended.
• Small talk starts 1.3 s before the greeting ended.

Possible causes:

• You may really have started that quickly.
• The recorded "question ended" time may be late. Kokoro's audio may have trailing silence, or the status change may lag.
• The speaker may be leaking into the microphone.

Plan: I don't want to guess a correction. I'd add a dev-only log of when the voice status changes and how long each line's audio is. One more short run would then show whether the end time is late, and by how much.

Questions for you

1. Time to first word: did you really start answering within a second most of the time? Did you start talking during the greeting?
2. "no no no I am done with discussion": did you mean "I've finished this answer", or "end the interview"? Neither is recognised by voice right now, and I'd add whichever you meant.
3. Things not in the log: did "Practice this one again", Save as PDF and the reload in the middle of the review work? Were there any console errors?

Expected (whisper-base mishearings): "conceptively" for constructively, "life cycle metad Henry I" for lifecycle method, "DatURL" for that URL. The report's footer covers this.

Proposed order: fixes 1 and 2 (intents), then 3 (guard), then 4 (measurements), each with tests. Then the timing log, then a short re-run. Shall I go ahead?

Fix 4, the measurements: ", like" before a pronoun, "Like I…" at the start of a sentence, and vague ranges such as "one or two".

I've made all four fixes from your run, plus the dev-only timing log. All 172 checks pass (22 of them new, using lines from your run). Type check, lint and build pass, the timing log isn't in the production build, and the report dev page still renders. Not committed yet.

1. Spoken skip.

• "Well, can you please skip this question?" now skips with no follow-up, and nothing is stored as an answer.
• Also recognised: "can we skip this one", "let's move on", "next question please", "skip it". These only count on a short stretch at the start of an answer; a long answer that mentions skipping stays an answer.
• Bug found along the way: pressing Skip during a follow-up marked an answered question as skipped. Skipping a follow-up (by voice or button) now just moves on, and the question stays answered.

2. "I don't know". "Sorry, I don't know about that." and "Honestly, I'm not sure." now count. Allowed openings before it: sorry, honestly, actually, well, oh, hmm, um, uh, so.

3. Off-target follow-ups.

• A "missing point" follow-up from Gemma now has to use one of the bank's own words for that point, or the written line is used instead.
• Both lines from your run are now rejected:
  • "how the DNS server handles the URL" (the missing point was parsing and rendering);
  • "how it helps with state management".
• Labels reworded: 30 key-point labels across 28 phrasings, so the written fallback reads as speech. For example, "Could you say a bit about runs after render, for side effects?" is now "…about what it is for and when it runs?". The matching words are unchanged.

4. Measurements.

• "like" with the comma before it is now a filler when a new clause follows. In your URL answer that's 3 more: "the, like we write", "browser, like it's a", "places, like suppose".
• "Like I took the feedback…" at the start of a sentence counts.
• "libraries, like React" still doesn't.
• Vague amounts ("one or two members", "two or three times", "a couple of") are no longer counted as numbers. That means the feedback answer would now get the "result marked covered, but no number heard" note.

5. Timing log (dev builds only). The Session log now has a timeline: when the voice status changes, when the interviewer's audio starts and stops being audible, when the mic hears sound, and when the detector closes a stretch. Each question's start time is listed too. On the next run this shows whether "question ended" is recorded late, and by how much, so we can fix it rather than guess.

For the re-run (about 3 minutes): commit first, then run a short interview in Chrome on localhost:5173 (phone screen, 2–3 questions).

• On one question, wait about 3 seconds after the interviewer finishes before you answer.
• On another, say "can we skip this one".
• Paste the Session log (it now includes the timeline).

Still open from before

1. Did you really start answering within about a second of most questions?
2. Did "I am done with discussion" mean "I've finished this answer" or "end the interview"? I haven't added either yet.
3. Did "Practice this one again", Save as PDF and the reload in the middle of the review work?

Shall I commit these fixes?

The page reloaded mid-script, so I'll run the capture again:

I've done the polish pass on the home and setup pages and sent you before and after screenshots at laptop (1280×800) and phone (375×812) width. Type check, lint, the 172 tests and the build all pass. Not committed yet.

Home page

• No outer card. The top section sits on the background. The background now has three soft colour glows (blue, violet, teal). They're as bright as they can go: any brighter and the muted text would drop below the 4.5:1 contrast rule in UX.md (it's 5.0:1 now at the brightest point).
• Top section: the name, one line ("Practice a real interview out loud, then look back at what you said"), and three points with small icons. "Never leaves your laptop" is one of them, and the privacy line moved up from the footer, which the home page no longer shows.
• Showing the product: a still of Ananya in the interview room, with a "Listening" chip and a question card. It's a real capture of the avatar, saved as two small images (about 20 KB and 26 KB) in src/assets/. They loaded from the browser cache, so nothing new was downloaded.
• Light and Heavy cards: bigger, with the download size large on each. The selected card has an accent border and a check. Light is selected by default. Heavy shows "Coming soon" and can't be picked; the switch is HEAVY_AVAILABLE in app/downloads.ts.
• Downloads: the total for the chosen mode is always shown ("1.6 GB the first time, plus 7 MB for a video interview"). The full table is under a closed "What downloads".
• Device check: now a small chip at the top. If the browser can't run the models, the full explanation still appears below the top section.
• Continue with Light: one primary button, in view without scrolling (bottom edge at 706 px of 800 on a laptop, 758 of 812 on a phone).
• Phone trade-off: to keep Continue in view, the room still moves below the choice, the points show titles only, and the cards show name, size and model side by side.
• Keyboard: arrow keys move between the cards (Heavy is skipped), Tab reaches Continue, and the focus ring shows.

Setup page

• Faces: the first step picks video or phone, then Ananya or Aarav, both as cards with their faces. After that, the interviewer card shows the chosen face.
• Loading: one compact area with a single size-weighted progress bar, "2 of 4 ready · 66%", and what's loading now. Each model's status is under a closed "Each model". When everything's ready it shrinks to "✓ Models ready · kept on this device".
• Selected chips: filled with the accent colour, with bold text. This also applies to the review's Covered/Partly/Missed chips.
• Two columns: on a laptop the options sit in two columns, with all helper lines kept, and the screen is wider (1040 px).
• Bottom bar: sticks to the bottom with Back and one primary button. That's Continue on the first step, then "Loading models · 66%" with the button filling up as the models load, then "Start interview".

What changed in behaviour, beyond looks:

• On the home page you now pick a mode and press Continue; before, clicking a card went straight on.
• Heavy can't be picked.
• The setup page's Continue moved into the bottom bar.

What I didn't check: a real model download and the microphone on the new setup screen. I used the dev preview's sample loading states (?dev=setup, &load=ready, &step=choose).

A font, if you want one (not added): Inter Tight or Manrope for headings only, from Google Fonts. That's about 20–30 KB, one weight, and a Google Fonts stylesheet works with our cross-origin isolation headers. The trade-off is one request to Google on page load, so the privacy wording would need a small change ("nothing you say leaves the device" stays true). I'd only add it if you want it; system fonts look fine.

Shall I commit this? Or tell me what to change first.

Both changes are in, and I've sent new screenshots at laptop and phone width. Type check, lint and build pass. Nothing is committed yet; this sits on top of the earlier polish.

Inter

• The whole app (headings and body) now uses Inter: one variable font file from Google Fonts covering every weight, with the system font shown until it loads.
• I checked it works under our cross-origin isolation headers: both Google requests return 200 and the page renders in Inter. The Render site sends the same headers, so it should behave the same there.
• Because the page now fetches a font from Google, the privacy wording no longer says "the only download is the models":
  • the footer now says "…the only downloads are the models (the first time) and the font";
  • README and UX.md say the same.
  • What you say still never leaves the device.
• If you'd rather the page make no requests to Google at all, I can bundle the font with the app instead. That needs one npm package (@fontsource-variable/inter), and I'd ask before installing it.

Downloads, now always visible

• Replaces the closed table: a "What Light downloads · 1.6 GB" breakdown.
• Bar: shows how the total splits across the models, in shades of the one accent colour.
• List: each model with what it does and its size: Gemma 3 1B 880 MB, Kokoro 326 MB, Whisper 295 MB, ONNX Runtime 67 MB, Silero VAD 1.8 MB.
• 3D avatar: listed separately as "+7 MB, video interview only", since it isn't in the total.
• Follows the choice: it updates with the selected mode (it will show Heavy's breakdown once Heavy can be picked).
• Laptop: the cards with Continue under them sit on the left, the breakdown on the right. Everything fits in 1280×800, with Continue's bottom edge at 721 px.
• Phone: cards, then Continue (in view at 705 px), then the breakdown right below it, then the room still.

Shall I commit the UI polish (home, setup, Inter and the downloads breakdown) as one commit?

I committed the UI polish as 2f9ff93: the home and setup pages, Inter, the downloads breakdown and the two avatar stills.

Nothing is pushed. main is now 10 commits ahead of GitHub: the README demo link, the report work (phase 1, steps 1–7), the fixes from your first real run, and this polish. Pushing redeploys the Render site, so I'll wait for you to say go.

Still open:

• Re-run: a short real interview to check the timing log and the fixes.
• Three questions from before:
  1. Did you really start answering within about a second of most questions?
  2. Did "I am done with discussion" mean "I've finished this answer" or "end the interview"?
  3. Did "Practice this one again", Save as PDF and the reload in the middle of the review work?
• Heavy: already shows as "coming soon". When it works, flip HEAVY_AVAILABLE in src/app/downloads.ts.

I've updated the task list and pushed to GitHub. main is up to date with origin/main (89ae844 → 7939211, 11 commits), and Entire's hook pushed 12 checkpoint refs alongside.

Task list (docs/TASKS.md):

• Phase 5: rewritten for the self-review direction, with 5.1–5.8 done.
• 5.9 (evidence finder): left open; that's phase 2 of the report plan, which waits for your go-ahead.
• Phase 6: marked done as you said. Notes on what that covers:
  • 6.2 lists the live Render link.
  • 6.1 notes that the voice detector files and the ONNX runtime still load from jsDelivr, so "offline" isn't fully true yet.
• Also done: 2.2 and 4.3 (your real run checked both), 7.5 (the fixes from that run), and a new 7.6 for the UI polish.
• Still open: 3.5 (re-running the evals), phase H (Heavy), 7.1–7.4 and phase 8.

Checked before pushing: no co-authored-by lines in the 11 commits, and the email address isn't in any of the 58 checkpoint commits.

Render deploys automatically on each commit, so the live site should pick up the new home, setup and report pages in a few minutes: https://interview-room-iooj.onrender.com

There's nothing left to push: everything went to GitHub in the last push (7939211), and main matches origin/main with no uncommitted changes.

Noted on the co-authored-by line. I'll add it to new commits from now on and won't rewrite the ones already pushed. Pushing still waits for your go-ahead each time.

I've rewritten README.md and added six screenshots in docs/images/. All image links resolve, and I checked the key numbers against the code (the 5 s answer pause, the 6 s Gemma limit, the dev pages). Nothing is committed or pushed yet.

What's in it, top to bottom

1. Intro: what it is, the privacy line (including the font), the live demo link, and the Build for a Friend note.
2. Home screenshot.
3. What it does: the interview out loud, pauses being fine, follow-ups chosen by rules and only worded by Gemma, video or phone, spoken commands and recovery, your own review, and the report with no scores.
4. Screenshots: setup and self-review side by side, then the report's things to work on, the charts and an answer card.
5. What the report measures: a table with each number and how it's measured, matching the report's footer.
6. Models: sizes and licences, Heavy marked "coming soon", the 1.6 GB first download, and the models being kept on the device.
7. How it works: a Mermaid diagram (GitHub draws it) from mic to voice detector, Whisper, the engine, Gemma, the guard and Kokoro, plus a line on each part of the code.
8. Run it locally: Node 20.19+ (this replaces the old, wrong "Node 18+", since Vite 8 needs 20.19), the commands one per block, and a table of the dev-only pages.
9. Deploy: the Render Blueprint.
10. react-ai-voice-avatar: says plainly that you maintain it and that the app is new, and lists the four 0.7.0 fixes made during the weekend.
11. Known limits:
    • Whisper base mishears technical terms;
    • Heavy isn't available yet;
    • it needs WebGPU on a laptop or desktop;
    • it isn't fully offline;
    • system design is parked.
12. Credits and licences, including Inter's licence (SIL Open Font License).

About the screenshots: they're 800 px wide, the largest the browser pane captures. That's fine for a README. For the post (task 8.2) you may want full-resolution ones from your own Chrome.

One line to check: "for a friend who practices interviews alone". Reword it if it doesn't fit how you'd describe your friend.

Shall I commit and push? New commits will include the co-authored-by line now.

I committed the README and the six screenshots as ec0d239, with the co-authored-by line, and pushed to GitHub. Entire's hook pushed 2 checkpoint refs with it, and main now matches origin/main.

The README is live at https://github.com/927tanmay/interview-room, where GitHub renders the screenshots and the diagram. Render will redeploy from this push too, but only the README changed, so the site stays the same.

Yes, there are a few real options. Here's what the code allows, and what I'd do given the deadline (12:29 IST today).

What's there now

• Model: the package runs the multilingual onnx-community/whisper-base, forced to English and "transcribe".
• No vocabulary hint: there's no way to give it a prompt, which is how Whisper is normally nudged towards spelling terms like "useEffect".
• Two settings we can use without touching the package:
  • asrModel, to pick a different Whisper;
  • onTranscribe(audio), which hands us the audio so we can transcribe it ourselves.

Mistakes from your run, by type

• Technical terms: "use effect" for useEffect, "life cycle metad" for lifecycle method.
• Similar-sounding words: "conceptively" for constructively, "DatURL" for that URL.
• Garble: "metad Henry I".

Options

A. Fix technical terms after transcription. No model, small effort.

• A glossary maps spoken forms to the right spelling: "use effect" → useEffect, "react query" → React Query, "java script" → JavaScript, "node JS" → Node.js, "post gres" → Postgres, and so on. It's built from a general list plus each question's own key words.
• Only joins words, splits them or fixes capitals; it never changes meaning.
• Matching key points with a little tolerance for spelling, so a misheard term still counts. That helps the follow-ups pick the right gap.
• Doesn't fix: garble like "metad Henry I".

B. Let you fix words during the review. Small effort.

• In the self-review, click a word in your answer to correct it. The report then uses your correction (with a small "edited" mark) and recalculates fillers and numbers.
• This fits the "you review your own answers" idea: honest, and it catches anything A misses.

C. A better Whisper, through asrModel. Needs a download.

• whisper-base.en: English-only, the same 295 MB, and usually more accurate in English. The risk is that the package always passes language: 'en', and English-only models can refuse that. It needs a 5-minute test before we rely on it.
• whisper-small.en: noticeably better with technical words. But it's several times bigger (up to about 1 GB, depending on the format the package picks, which we can't set) and slower. It may suit Heavy mode later.

D. Our own Whisper, given the question's vocabulary. The most effective, and the most work.

• Use onTranscribe to run Whisper in our own worker. Before each answer, give it the current question's terms ("useEffect, dependency array, cleanup").
• To check first:
  • whether transformers.js supports Whisper prompts in the browser;
  • whether the package skips loading its own Whisper when onTranscribe is set (otherwise two copies in memory).
• Not for today.

E. Have Gemma rewrite the transcript. I'd rule this out: a 1B model would invent words, and the report promises your own words.

My recommendation for today:

1. A and B now. No downloads, low risk, and B covers anything A misses.
2. C (whisper-base.en) if you're happy for me to download 295 MB to test it. If it accepts the forced language and is more accurate on your kind of answers, it's a one-line switch.
3. D after the challenge.

Which would you like? A and B, plus testing C?

Sounds good, we'll leave Whisper as it is. Switching models later is easy: asrModel takes a different Whisper with no package change (try whisper-base.en first). For the bigger improvement, giving Whisper each question's vocabulary through onTranscribe is the one to explore after the challenge.

If you want, I can note both under "P2, only if time" in docs/TASKS.md so they aren't lost; it's a two-line change.

I've added both speech-recognition steps under "P2, only if time" in docs/TASKS.md:

• Step 1: switch Whisper with asrModel, starting with whisper-base.en. It includes checking that it accepts the forced English setting, and asking before downloading.
• Step 2: run our own Whisper through onTranscribe, giving it each question's vocabulary. It includes the two things to check first.

It isn't committed. Shall I commit and push it, or leave it for the next batch of changes?

I'll update PLAN.md to match where things are now. First I'll read it to see what's out of date:

I updated both files, committed them as f491280 with the co-authored-by line, and pushed to GitHub. main matches origin/main.

docs/PLAN.md

• Report section: rewritten for the new direction. You review your own answers and the app never judges; it covers what's measured, the things-to-work-on rules, the second looks, the per-answer cards, and phase 2 (the embedding helper) not yet started.
• Setup and interview: system design parked; own questions, questions from a job description, and the privacy meter marked "later, not built".
• Models: Heavy shown as "coming soon" (HEAVY_AVAILABLE), and a note that Whisper mishears some technical terms.
• Who does what: judging is now yours, in the self-review; Gemma only words the follow-up.
• Priorities and timeline:
  • P0 marked done, plus the deploy and the UI polish;
  • P1 not built yet;
  • a new "actual" row for what was done on 4 Oct.
• Guard and recovery: the missing-point check, spoken skip and "sorry, I don't know". Tough interrupting is marked as P2, not built.
• Hacktoberfest checklist:
  • ticked: repo public, credits and licences in the README, the demo link;
  • still open: credits in the post, the video, and the other items.
• Open decisions:
  • closed: Light's report, Entire, Backboard;
  • added: whether to turn Heavy on for the submission, and the better Whisper for later.

docs/TASKS.md

• 8.1 (README) marked done.
• The two speech-recognition steps added under P2.

Still open for the submission: 8.2 (demo video or GIF), 8.3 (your friend tries it) and 8.4 (the post, due by about 11:00 today).

The live site is on the latest build: it loads Inter, which came with the UI polish, and it sends both cross-origin isolation headers. The README and PLAN.md commits after that didn't change the app, so what you record on https://interview-room-iooj.onrender.com is current.

Before you record:

• Heavy is "coming soon" on the home page, so record Light.
• First load: if this Chrome profile hasn't loaded the Render site before, the first visit downloads about 1.6 GB. Opening it once before you record will make the video start fast.
• Report: after the interview comes the self-review, then the report. Both are worth showing; Save as PDF and "Practice this one again" are good closing shots.

Once you've uploaded the video, send me the link and I'll add it to the README and push.

Sounds good, the video is yours to add. The working tree is clean and matches GitHub, so you can add the video link to the README and push without conflicts.

If you want a hand with the submission post (8.4), the README and PLAN.md already have most of what it needs: the friend story, the models, the "rules decide, Gemma speaks" design, the measured numbers, and the credits.

I've fixed the frozen loading screen and pushed it (fd21d3e). The new build should be live on Render in a few minutes; I'm checking the site in the background and will tell you when it's up. One caveat: I couldn't block Hugging Face in my browser pane, so the real network failure hasn't been tested end to end yet (details under "How I tested").

What was wrong

• Whisper: a failed Whisper download is reported by the package's worker start-up step, with the stage "worker". We only listened for "speech-recognition", so the failure was never caught. That's the endless 21%.
• Kokoro: a failed Kokoro is reported only as "degraded" while the package quietly switches to its backup MMS voice. We ignored anything that wasn't "fatal".

What it does now

• Says what failed, in plain words. For example: "The interviewer's voice (Kokoro) didn't finish loading. The interview won't start on a backup voice, so try again to get the real one." Then: "This is usually a dropped connection. Files that finished are kept on this device, so trying again picks up where it stopped." The package's raw message goes to the console only.
• Try again, retrying only what failed. The button appears in the loading area, and the sticky bar's main button becomes "Try again" too.
  • Whisper, Kokoro or the avatar: a fresh voice engine starts, back on Kokoro, and finished files come from storage.
  • Gemma: only Gemma reloads.
• No interview on the backup voice. If Kokoro failed, Start stays off until Kokoro loads on a retry.

The two small ones

• The microphone notice no longer repeats the raw message in brackets.
• Phone-sized touch screens get one line on the home page: "Built for a laptop. On a phone it would download 1.6 GB and probably can't run it." It's hidden on laptops.

How I tested: my browser pane has no DevTools network conditions, and service workers are disabled in it, so I couldn't block Hugging Face there. Instead:

1. Error mapping: 8 new checks feed the handler the exact error shapes the package sends, which I read in its code. A Whisper failure at worker start-up and the quiet Kokoro fallback are both now marked failed, and the backup voice coming up doesn't count as Kokoro ready. All 180 checks pass.
2. Real first-visit download in the pane:
   • Failing partway: at 7% I injected those package errors for Whisper and Kokoro, plus a Gemma failure. The screen showed all three in plain words with "Try again".
   • Retrying: "Try again" started a fresh engine and reloaded Gemma, and all three loaded to "✓ Models ready", with "Start interview" enabled.
   • Retrying only what failed: failing Gemma alone restarted only Gemma; Whisper and Kokoro carried on from 52 and 29 MB.

Worth doing yourself, if you have 5 minutes: the real block in Chrome, on a profile that hasn't loaded the site before.

1. Open DevTools → Network → Network request blocking, and add huggingface.co.
2. Pick Light, then phone screen, then Continue. Whisper and Kokoro should come up as failed in plain words.
3. Untick the block, then press "Try again".

Two gaps left alone, since you said no more features:

• If storage is full (as in my pane), "Models ready · kept on this device" still shows even though nothing was kept.
• If Kokoro fails mid-interview, after it had loaded, the package still switches to the backup voice without saying so.

The fix is now live at https://interview-room-iooj.onrender.com: the new build (index-CmYdnwON.js) went up about 45 seconds after the push, and its code includes the new failure messages. The Chrome check with Hugging Face blocked, from my last message, will run against this build.

Each answer card now has a "Next time" list, and it's pushed (58c1967). Render will deploy it within a minute or two. I've sent you the screenshot.

How it works

• One line per point she marked missed, then the ones marked partly.
• Wording comes from the point's tag, as an action:
  • Result: "Say how it turned out, with a number if you have one".
  • Your role: "Say what you did yourself".
  • The other tags: "Set the scene in a sentence or two", "Give a concrete example", "Cover what happens when something goes wrong", "Mention the trade-off", and so on.
• Stays specific: the point's own text follows in muted brackets, e.g. "Say what you did yourself (the part you personally owned)". Partly-covered points add "· you covered part of this".
• When it doesn't show: when nothing was missed or partly, and when the self-review was skipped.
• Look: it follows UX.md, with the same label style as "Your marks", accent bullets, and no new colours.

Checked: 7 new checks cover the wording, the order, the empty cases, the skipped review, and acronyms like "DNS" keeping their capitals; all 187 pass. Type check, lint and build pass. On ?dev=report with a new fake interview, the two answers with missed points got lists; the skipped question and the all-covered answer showed none.

Left alone: .entire/settings.json shows a change I didn't make, probably from Entire itself. I didn't commit it.

I'm stopping here, with no other changes before the deadline.