From coquill
Transcript generator for CoQuill. Reads an interview_log.json and manifest.yaml, then writes a human-readable transcript.md to the job folder. Called by the coquill orchestrator — not triggered directly by the user.
How this skill is triggered — by the user, by Claude, or both
Slash command
/coquill:coquill-transcriberThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You generate a transcript from a completed interview session. The heavy lifting
You generate a transcript from a completed interview session. The heavy lifting
is handled by scripts/transcribe.py; your job is to invoke it and relay the result.
interview_log_path — path to interview_log.json in the job foldermanifest_path — path to manifest.yaml in the template directoryjob_folder — path to the job output folderoutput_files — comma-separated output file basenames (e.g., agreement.docx, agreement.pdf)ended_at — ISO 8601 timestamp for when the document was renderedThe interview log records the substance of each exchange, not a literal word-for-word
transcript of every micro-turn. When a user answered multiple questions at once, the log
records the net result. The clarification entry handles the exceptional case where
the user asked a substantive question about the document before answering.
Resolve the script path relative to the project root and invoke it:
python scripts/transcribe.py \
--interview-log <interview_log_path> \
--manifest <manifest_path> \
--job-folder <job_folder> \
--output-files "<output_files>" \
--ended-at "<ended_at>"
The script reads both files, builds the four transcript sections (header, interview,
confirmed values, footer), writes transcript.md to the job folder, and prints a
JSON result to stdout.
The script prints JSON: {"transcript_path": "...", "success": true} on success,
or {"transcript_path": null, "success": false, "error": "..."} on failure.
npx claudepluginhub houfu/coquill --plugin coquillTranscribes audio/video files to text using Faster-Whisper or Whisper, generating structured meeting minutes, executive summaries, and subtitle files (SRT, VTT).
Transcribes audio/video files to Markdown documentation with LLM summaries, speaker diarization, timestamps, and meeting minutes using Faster-Whisper or Whisper.
Processes meeting transcripts from Fireflies into structured discussion documents with optional ADR extraction. Lists undocumented meetings or batches all for import.