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extracting-structure

extracting-structure

The user wants structure pulled out of a watched video — "make chapters for this video", "where does the bug appear in this recording", "turn this screen recording into a bug report", "how strong is my intro/hook". Use this for deterministic extraction from the index — chapters with timestamps, a fileable bug report with the exact frame, or a scored hook an…

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name: extracting-structure version: "1.4.3" description: The user wants structure pulled out of a watched video — "make chapters for this video", "where does the bug appear in this recording", "turn this screen recording into a bug report", "how strong is my intro/hook". Use this for deterministic extraction from the index — chapters with timestamps, a fileable bug report with the exact frame, or a scored hook analysis. license: MIT user-invocable: true allowed-tools: Bash, Read

Extracting structure

Three extractors turn an already-watched video into something structured. All of them answer straight from the persistent index — deterministic, no extra model calls. The video must be watched first (see watching-videos).

Chapters

watch-skill extract chapters <video_id-or-source>

Titled chapters with start/end timestamps, built from scene changes plus transcript topic shifts. Good for long tutorials, lectures, meetings — give the user the chapter list with timestamps, not a prose summary.

Bug report from a screen recording

watch-skill extract bug-report <video_id-or-source>

Pinpoints where an error appears: timestamp, the exact frame, the on-screen error text as OCR read it, and the steps that led up to it (from the transcript/actions preceding the failure). Returns found: false honestly when no error signal exists — report that as "no error found in the recording", not as an error.

Paste the output into the user's issue tracker format when they ask for a fileable report; the frame path is the attachment.

Hook analysis (creators)

watch-skill extract hook <video_id-or-source> [--seconds 15]

Scores the opening seconds on four measured axes — attention trigger in the opening line, speech pacing, visual change rate, on-screen text — each with an actionable critique, plus a 0–100 score and verdict. Give the user the per-axis critiques; the number alone helps nobody.

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