--- name: transcribe description: Capture, transcribe, import, attribute, and review advisor voice notes, consultant debriefs, meetings, calls, and existing audio recordings with Clara Hosted Voice. Use when the user asks to start Voice Capture, transcribe an audio file, import a case-notes-audio or case-notes-voice ZIP/JSON bundle, preserve a transcript in an ordinary folder with deduplication, or add a reviewed transcript to a Clara case. Do not use to create an adaptive external-participant interview link or to revise a deck from spoken feedback. --- Onboarding is optional. Continue ordinary professional work immediately, including direct specialist invocation, without checking or completing a local onboarding profile. Missing, unfinished, inaccessible or corrupt onboarding state, or unavailable voice/window controls, must never block ordinary work. Do not automatically start, resume or repeatedly offer onboarding. Only for a user-requested tutorial or a native teaching handoff, read `../clara/references/local-onboarding.md`. A verified paired lesson worker executes only its bound lesson and token; never bypass tutorial validation. Tutorial profiles, progress, examples and feedback remain local; never send a change request, stamp a tutorial receipt or call hosted interviews for a tutorial. Current user requests take precedence over saved preferences. # Transcribe After substantive use of this workflow, read and follow the `Plugin Improvement Feedback` section in `../clara/SKILL.md`. ## Output Location Rule Never write run outputs inside this Git workspace, `static/shared`, `protected_downloads`, or another static-site folder. Preserve bundles, audio, transcripts, review files, and `codex_run_review.md` in the user's target case, ordinary folder, or adjacent project/output folder. Use this skill for transcription-first evidence capture. The hosted service is the authorized audio/transcription layer. Durable source and output files remain local after import; Codex performs speaker review and advisory interpretation through the user's existing ChatGPT plan. This is separate from `hosted-interview`, which conducts an adaptive conversation with an external participant. ## Choose the Path - **Live consultant debrief:** launch Voice Capture from an existing Clara case. - **Existing audio:** upload the voice note, meeting, or call recording through the hosted service, then import the downloaded bundle. - **Downloaded bundle into a Clara case:** import into `voice_sessions/`, finish speaker attribution, register the reviewed transcript, and update the case evidence map before downstream advisory output. - **Downloaded bundle into an ordinary folder:** preserve the original bundle and readable transcript with deduplication; do not initialize a case merely to store the transcript. - **Spoken feedback that should change a deck:** complete transcription and attribution here, then route the reviewed evidence to `deck-correction`. In a case using advisory lineage, the reviewed transcript creates an `interview_transcript` receipt with the transcript path, locator, and hash. Each quote or attribution used downstream becomes a claim linked to that receipt. The receipt can establish that the named speaker said the quoted words; it does not by itself establish that the speaker's underlying assertion is true. Create a separate claim and basis when Clara relies on the assertion as a fact. Preserve the same claim and evidence IDs when the quote moves into a workpaper, memo, decision pack, Claim Basis Map, or HTML content ledger. Run dependency checks from the plugin directory before substantive work: ```bash python scripts/check_dependencies.py ``` Install declared requirements only when the environment permits. Do not install packages at runtime from within a plugin script. ## Live Capture For an initialized Clara case: ```bash python scripts/launch_hosted_voice.py python scripts/launch_hosted_voice.py --browser chrome python scripts/launch_hosted_voice.py \ --cookie-header-file ``` With an authenticated cookie or magic link, the launcher refreshes `case_brief.md`, sends compact transcription context in an authenticated HTTPS request body, and opens the hosted page with an opaque short-lived token. The context is not placed in the URL. The user-bound token is an additional session control and does not replace Mparanza authentication. Without supplied authentication material, the launcher opens an explicit browser-authenticated fallback without reading or attaching `case_brief.md`. Use Chrome when the embedded browser or stale permissions block the microphone. The browser downloads a local bundle when the session ends. Directly opening the hosted voice URL without a plugin-created launch token and authenticated session is not a valid run. Voice Capture is transcription-first. Sparse follow-ups may help the advisor finish a debrief, but the hosted model is not the final speaker-attribution or advisory authority. ## Existing Audio The hosted page accepts an existing audio recording. When browser upload is blocked or the file is large, use the authenticated uploader: ```bash python scripts/upload_hosted_audio.py \ --magic-link-file python scripts/upload_hosted_audio.py \ --cookie-header-file ``` Add source metadata such as `--title`, `--interview-date`, `--participants`, and `--interviewer` when known. Do not place authentication secrets in chat or run artifacts. The uploader stores the returned bundle under the case workspace and normally imports it immediately. Use `--no-import` only when the bundle must be inspected before registration. For an ordinary folder that is not a Clara case, disable both case-dependent behaviors and choose the transcription language explicitly when it is not Italian: ```bash python scripts/upload_hosted_audio.py \ --no-case-context --no-import --language ar \ --magic-link-file ``` `--language` is the language spoken in the recording, not the language of the case or final deliverable. For an Arabic recording, use `--language ar` and preserve the returned Arabic transcript. A Clara case may still use English, Italian, French, German, or Spanish as its output language; downstream notes, analysis, and deliverables follow that case language. Do not silently replace the Arabic source transcript with a translation. The uploader saves the returned bundle under `/hosted_voice_uploads/`. Import that bundle with the ordinary folder importer below. If `case_manifest.json` exists, the uploader continues to require a valid Clara case workspace. ## Import Into a Clara Case Use the newest valid download by default: ```bash python scripts/import_latest_hosted_voice_bundle.py ``` Point to a specific bundle only when necessary: ```bash python scripts/import_hosted_voice_bundle.py ``` The importer preserves the raw payload and media, registers the transcript as source material, creates a local review pack, and prevents repeated imports of the same session. Treat the imported transcript as evidence, not final advice. ## Import Into an Ordinary Folder When the target does not contain `case_manifest.json` and the user only wants a durable transcript: ```bash python scripts/import_hosted_voice_bundle_to_folder.py \ ``` This path keeps or adopts the original ZIP/JSON, writes or adopts a readable sibling transcript, and records relative paths and SHA-256 fingerprints in `.clara/voice_imports.json`. Exact or repackaged duplicates reuse existing artifacts. Missing transcripts may be repaired. Never overwrite or delete an ordinary-folder document; unrelated collisions receive numeric suffixes. A conflicting variant requires deliberate `--allow-variant` use. This lightweight path does not create case JSON, infer speakers, register judgement, or promote the transcript into advisory evidence. ## Speaker Attribution and Review The hosted server transcribes audio; it is not the speaker-naming authority. Import may create `attributed_transcript.md` only when a single known speaker makes attribution trivial. Otherwise it creates `speaker_attribution_task.md` and `speaker_attribution_report.json`. Codex must complete that task in the same workflow: 1. Read the raw transcript, source metadata, and useful notes. 2. Assign real names only when supported; otherwise use stable labels such as `Speaker 1` and `Speaker 2`. 3. Preserve the original unattributed transcript. 4. Correct only obvious transcription errors whose intended wording is clear from context or a trusted case glossary. 5. Inspect for merged turns or wrong labels and keep uncertainty visible. Do not use an audio diarization model for Clara speaker attribution. Do not rewrite, summarize, or change meaning during the transcript-cleaning pass. Finalize a reviewed transcript with the deterministic registry helper: ```bash python scripts/finalize_hosted_transcript.py \ \ \ --audio-pointer ``` Finalization also creates a content-hash-stable `interview_transcript` evidence receipt for the exact reviewed transcript bytes. It records that the transcript supports attributed wording only; it does not promote the speaker's underlying assertion into a fact. When the reviewed transcript also requires judgement, questions, and live-issue updates, Codex drafts a semantic integration plan and applies it with: ```bash python scripts/integrate_transcript_review.py \ --plan-json ``` The semantic plan includes any new `evidence_receipts`, `claims`, judgement entries, open-question links, and case-issue claim links. The helper applies the whole plan atomically; it does not interpret the transcript. New judgement remains `pending` until the advisor makes the normal client-pack inclusion decision, and it cannot later be approved without its canonical claim binding. Update `advisory_evidence_map.md` before the transcript changes a workpaper, storyline, deck, memo, or decision pack. ## Codex-Native Run UX Use a short checklist covering source selection, hosted capture or upload, bundle import, speaker attribution, transcript review, registry finalization, and case-evidence update. Show a compact Run Intake table with source recording or capture mode, target case/folder, language, known speakers, source metadata, bundle path, and output folder. Use a Decision Table only for unresolved material choices such as an ambiguous target folder, a genuinely uncertain speaker boundary, or whether a conflicting recording is an intentional variant. Default output policy: preserve the source bundle and audio, produce a readable reviewed transcript, and register it when the target is a Clara case. These are not choices to propose when the user asked for the normal transcription run. Speaker attribution is the approval checkpoint before advisory or deck use; do not ask for ceremony when attribution is clear from inspected evidence. Before long or write-heavy work, show an execution checkpoint naming the source, target folder, expected local artifacts, and whether hosted upload is required. End with an Artifact Card listing source bundle, audio, raw transcript, reviewed transcript, attribution status, registry status, and unresolved uncertainty. Create `codex_run_review.md` only for a blocked run or a repeatable import or transcription gap. Never edit generated ZIPs during a run.