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 analysis.
- Installs
- 522
- Last 24h
- +17
- Trending rank
- #6444
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/oxbshw/watch-skill --skill extracting-structure- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads extracting-structure automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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.
FAQ
What does the extracting-structure skill do?
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.
How do I install extracting-structure?
Run npx skills add https://github.com/oxbshw/watch-skill --skill extracting-structure in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/extracting-structure/ (personal) or .claude/skills/extracting-structure/ (project).
Which AI agents can use extracting-structure?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is extracting-structure safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains extracting-structure?
It is published by oxbshw in oxbshw/watch-skill. It has 522 recorded installs.
More from oxbshw/watch-skill
watch
oxbshw/watch-skill
Watch any video (URL, stream, or local path) via Watch Skill. Downloads, extracts scene-aware deduped frames, OCRs them, transcribes (captions first, then local Whisper — offline by default), indexes everything, and hands the result to the agent. Follow-up questions are answered from the persistent index without re-processing.
watching-videos
oxbshw/watch-skill
The user shared a video URL, a YouTube/TikTok/stream link, a local video file, a screen recording, a meeting recording, or a playlist/folder of videos — "watch this", "summarize this video", "what's in this recording". Use this to actually watch the video — download, extract frames, OCR, transcribe, and index it — instead of guessing from the title or asking the user to describe it.
video-memory
oxbshw/watch-skill
The user asks about videos watched in the past or across sessions — "have we watched anything about X", "which video showed that error", "what did that meeting decide", "search my videos", or a question that spans several videos. Use this to search and answer from the persistent cross-video index instead of saying you don't remember.
asking-with-evidence
oxbshw/watch-skill
The user asks a question about a video that was already watched or indexed — "what did they say about X", "what error code appears", "what happens at 2:30", "does the video show Y". Use this to answer from the persistent index with timestamped evidence and a confidence score instead of re-watching or guessing.
the-loop
oxbshw/watch-skill
The user built or changed something visual — a UI, an animation, a game, a generated video — and wants it verified, or asks "why does my UI look wrong", "check that the fix actually worked", "does the animation glitch". Use this to record the running thing, critique the recording against plain-language pass criteria, and iterate until it passes with before/after proof.
recovering-from-errors
oxbshw/watch-skill
A Watch Skill command failed, video download broke, ffmpeg or yt-dlp is missing, a provider returned an error, local vision stopped, or the user asks "why can't it watch this" or "repair my setup". Use this to diagnose and apply the engine's structured fix before retrying the original operation.
Popular code quality & workflow skills
grill-me
mattpocock/skills
A relentless interview to sharpen a plan or design.
improve-codebase-architecture
mattpocock/skills
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
handoff
mattpocock/skills
Compact the current conversation into a handoff document for another agent to pick up.
domain-modeling
mattpocock/skills
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.
codebase-design
mattpocock/skills
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
diagnosing-bugs
mattpocock/skills
Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.