| name | talkthrough |
| description | Analyze narrated screen recordings and audio files — timestamped transcript, scene keyframes, OCR text, and wall-clock anchoring via the local talkthrough MCP server. Use when the user shares a recording or asks to triage feedback, extract meeting actions, or correlate a recording with logs. |
talkthrough for OpenClaw
This skill wires the talkthrough MCP server into OpenClaw and teaches the
workflow. Everything runs locally: recordings never leave the machine.
Setup (once)
Add the MCP server:
openclaw mcp add talkthrough --command uvx --arg talkthrough-mcp[diarization]
Requires uv (https://astral.sh/uv). First processing downloads a whisper
model once (~460 MB for the default small).
Workflow
process_media(path) — idempotent by content hash; returns a compact
summary with job_id (re-calls on the same file are instant).get_transcript(job_id) / search(job_id, "<word>") — orient; search
covers speech AND on-screen OCR text.get_moment(job_id, t0-2000, t1+2000) — evidence bundle per remark:
transcript slice + up to 3 frames + OCR + wall-clock range.extract_frame(job_id, at_ms, crop=...) — exact instant, native
resolution, when keyframes miss the moment.list_jobs() — recordings processed earlier remain queryable.
Timestamps: t_ms is video-relative; t_wall is real wall-clock time when
the recording start is known — use it to correlate remarks with logs
(±30 s window). Audio-only files (.m4a/.mp3/…) have transcripts but no
frames; frame tools erroring on them is expected.
Full docs: https://github.com/korovin-aa97/talkthrough-mcp
