π¦ ClawHub
Video Skill
by @michaelgold
Run the video-skill pipeline to convert narrated videos into structured step data and enriched timeline-ready outputs. Use when a user asks to process a vide...
TERMINAL
clawhub install video-skillπ About This Skill
name: video-skill description: Run the video-skill pipeline to convert narrated videos into structured step data and enriched timeline-ready outputs. Use when a user asks to process a video into steps, run transcription/chunking/extraction/enrichment, debug provider connectivity, or generate markdown from extracted skills. metadata: { "openclaw": { "requires": { "bins": ["uv", "ffmpeg", "python3"] } } }
Video Skill
Use this skill to run video-skill end-to-end or stage-by-stage.
First-time setup (no repo clone required)
Use one of these setup paths:
A) Run from local source repo (recommended while iterating):
cd /path/to/videoskill
uv sync --dev
cp config.example.json config.json
Then run commands with uv run, for example:
uv run video-skill --help
Then run video-skill ... directly from your working directory.
Verify providers before processing:
video-skill config-validate --config config.json
video-skill providers-ping --config config.json --path /v1/models
Standard workflow (recommended)
Run from your working directory where config.json and data paths are valid.
video-skill transcribe --video --out .whisper.json --config config.json
video-skill transcript-parse --input .whisper.json --out .segments.jsonl
video-skill transcript-chunk --segments .segments.jsonl --out .chunks.jsonl --window-s 120 --overlap-s 15
video-skill steps-extract --segments .segments.jsonl --clips-manifest .jsonl --chunks .chunks.jsonl --mode ai --config config.json --out .steps.ai.jsonl
video-skill frames-extract --video --steps .steps.ai.jsonl --out-dir --manifest-out .frames_manifest.jsonl --sample-count 2
video-skill steps-enrich --steps .steps.ai.jsonl --frames-manifest .frames_manifest.jsonl --out .steps.enriched.ai.jsonl --mode ai --config config.json
video-skill markdown-render --steps .steps.enriched.ai.jsonl --out .md --title ""
</code></pre></p><p style="margin:8px 0"><h3 style="color:#e5e7eb;margin:18px 0 8px;font-size:1.05em">Modes</h3></p><p style="margin:8px 0"><li style="color:#94a3b8;margin:3px 0"><code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">--mode heuristic</code>: deterministic, no model calls</li>
<li style="color:#94a3b8;margin:3px 0"><code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">--mode ai-direct</code>: VLM-centric enrichment</li>
<li style="color:#94a3b8;margin:3px 0"><code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">--mode ai</code>: reasoning + VLM orchestration (default for quality)</li></p><p style="margin:8px 0">Prefer <code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">--mode ai</code> unless user asks for debugging or reduced model usage.</p><p style="margin:8px 0"><h3 style="color:#e5e7eb;margin:18px 0 8px;font-size:1.05em">Reliability and diagnostics</h3></p><p style="margin:8px 0"><code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">steps-enrich</code> emits:
<li style="color:#94a3b8;margin:3px 0">per-step progress logs</li>
<li style="color:#94a3b8;margin:3px 0">summary metrics: <code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">parse_errors</code>, <code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">transient_recovered</code>, <code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">unresolved_final</code></li>
<li style="color:#94a3b8;margin:3px 0">detailed <code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">*.errors.jsonl</code> when any errors occur</li></p><p style="margin:8px 0">If runs fail unexpectedly:
1. re-run <code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">providers-ping</code>
2. inspect <code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">*.errors.jsonl</code> by stage (<code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">sampling_plan</code>, <code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">vlm_judge</code>, <code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">vlm_select_frames</code>, <code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">vlm_signal_pass</code>, <code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">reasoning_finalize</code>)
3. verify endpoint DNS/host reachability</p><p style="margin:8px 0"><h3 style="color:#e5e7eb;margin:18px 0 8px;font-size:1.05em">Validation gate before claiming success</h3></p><p style="margin:8px 0">Always run:</p><p style="margin:8px 0"><pre style="background:#0a0a1c;border:1px solid #1e1e3f;border-radius:6px;padding:10px 12px;overflow-x:auto;font-size:.9em;margin:8px 0"><code style="color:#a5f3fc;background:none;padding:0;font-size:1em">video-skill --help
</code></pre></p><p style="margin:8px 0">Use <code style="background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em">make verify</code> only when working from the source repo.
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Use when a user asks to process a video into steps, run transcription/chunking/extraction/enrichment, debug provider connectivity, or generate markdown from extracted skills.\nmetadata: { \"openclaw\": { \"requires\": { \"bins\": [\"uv\", \"ffmpeg\", \"python3\"] } } }\n\u003chr style=\"border:none;border-top:1px solid #1e1e3f;margin:12px 0\"\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003ch2 style=\"color:#f3f4f6;margin:20px 0 10px;font-size:1.15em\"\u003eVideo Skill\u003c/h2\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003eUse this skill to run \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003evideo-skill\u003c/code\u003e end-to-end or stage-by-stage.\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003ch3 style=\"color:#e5e7eb;margin:18px 0 8px;font-size:1.05em\"\u003eFirst-time setup (no repo clone required)\u003c/h3\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003eUse one of these setup paths:\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003cstrong style=\"color:#e5e7eb\"\u003eA) Run from local source repo (recommended while iterating):\u003c/strong\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003cpre style=\"background:#0a0a1c;border:1px solid #1e1e3f;border-radius:6px;padding:10px 12px;overflow-x:auto;font-size:.9em;margin:8px 0\"\u003e\u003ccode style=\"color:#a5f3fc;background:none;padding:0;font-size:1em\"\u003ecd /path/to/videoskill\nuv sync --dev\ncp config.example.json config.json\n\u003c/code\u003e\u003c/pre\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003eThen run commands with \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003euv run\u003c/code\u003e, for example:\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003cpre style=\"background:#0a0a1c;border:1px solid #1e1e3f;border-radius:6px;padding:10px 12px;overflow-x:auto;font-size:.9em;margin:8px 0\"\u003e\u003ccode style=\"color:#a5f3fc;background:none;padding:0;font-size:1em\"\u003euv run video-skill --help\n\u003c/code\u003e\u003c/pre\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003eThen run \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003evideo-skill ...\u003c/code\u003e directly from your working directory.\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003eVerify providers before processing:\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003cpre style=\"background:#0a0a1c;border:1px solid #1e1e3f;border-radius:6px;padding:10px 12px;overflow-x:auto;font-size:.9em;margin:8px 0\"\u003e\u003ccode style=\"color:#a5f3fc;background:none;padding:0;font-size:1em\"\u003evideo-skill config-validate --config config.json\nvideo-skill providers-ping --config config.json --path /v1/models\n\u003c/code\u003e\u003c/pre\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003ch3 style=\"color:#e5e7eb;margin:18px 0 8px;font-size:1.05em\"\u003eStandard workflow (recommended)\u003c/h3\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003eRun from your working directory where \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003econfig.json\u003c/code\u003e and data paths are valid.\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003cpre style=\"background:#0a0a1c;border:1px solid #1e1e3f;border-radius:6px;padding:10px 12px;overflow-x:auto;font-size:.9em;margin:8px 0\"\u003e\u003ccode style=\"color:#a5f3fc;background:none;padding:0;font-size:1em\"\u003evideo-skill transcribe --video \u003cvideo.mp4\u003e --out \u003cname\u003e.whisper.json --config config.json\nvideo-skill transcript-parse --input \u003cname\u003e.whisper.json --out \u003cname\u003e.segments.jsonl\nvideo-skill transcript-chunk --segments \u003cname\u003e.segments.jsonl --out \u003cname\u003e.chunks.jsonl --window-s 120 --overlap-s 15\nvideo-skill steps-extract --segments \u003cname\u003e.segments.jsonl --clips-manifest \u003cclips\u003e.jsonl --chunks \u003cname\u003e.chunks.jsonl --mode ai --config config.json --out \u003cname\u003e.steps.ai.jsonl\nvideo-skill frames-extract --video \u003cvideo.mp4\u003e --steps \u003cname\u003e.steps.ai.jsonl --out-dir \u003cframes_dir\u003e --manifest-out \u003cname\u003e.frames_manifest.jsonl --sample-count 2\nvideo-skill steps-enrich --steps \u003cname\u003e.steps.ai.jsonl --frames-manifest \u003cname\u003e.frames_manifest.jsonl --out \u003cname\u003e.steps.enriched.ai.jsonl --mode ai --config config.json\nvideo-skill markdown-render --steps \u003cname\u003e.steps.enriched.ai.jsonl --out \u003cname\u003e.md --title \"\u003cTitle\u003e\"\n\u003c/code\u003e\u003c/pre\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003ch3 style=\"color:#e5e7eb;margin:18px 0 8px;font-size:1.05em\"\u003eModes\u003c/h3\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003cli style=\"color:#94a3b8;margin:3px 0\"\u003e\u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003e--mode heuristic\u003c/code\u003e: deterministic, no model calls\u003c/li\u003e\n\u003cli style=\"color:#94a3b8;margin:3px 0\"\u003e\u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003e--mode ai-direct\u003c/code\u003e: VLM-centric enrichment\u003c/li\u003e\n\u003cli style=\"color:#94a3b8;margin:3px 0\"\u003e\u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003e--mode ai\u003c/code\u003e: reasoning + VLM orchestration (default for quality)\u003c/li\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003ePrefer \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003e--mode ai\u003c/code\u003e unless user asks for debugging or reduced model usage.\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003ch3 style=\"color:#e5e7eb;margin:18px 0 8px;font-size:1.05em\"\u003eReliability and diagnostics\u003c/h3\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003esteps-enrich\u003c/code\u003e emits:\n\u003cli style=\"color:#94a3b8;margin:3px 0\"\u003eper-step progress logs\u003c/li\u003e\n\u003cli style=\"color:#94a3b8;margin:3px 0\"\u003esummary metrics: \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003eparse_errors\u003c/code\u003e, \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003etransient_recovered\u003c/code\u003e, \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003eunresolved_final\u003c/code\u003e\u003c/li\u003e\n\u003cli style=\"color:#94a3b8;margin:3px 0\"\u003edetailed \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003e*.errors.jsonl\u003c/code\u003e when any errors occur\u003c/li\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003eIf runs fail unexpectedly:\n1. re-run \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003eproviders-ping\u003c/code\u003e\n2. inspect \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003e*.errors.jsonl\u003c/code\u003e by stage (\u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003esampling_plan\u003c/code\u003e, \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003evlm_judge\u003c/code\u003e, \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003evlm_select_frames\u003c/code\u003e, \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003evlm_signal_pass\u003c/code\u003e, \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003ereasoning_finalize\u003c/code\u003e)\n3. verify endpoint DNS/host reachability\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003ch3 style=\"color:#e5e7eb;margin:18px 0 8px;font-size:1.05em\"\u003eValidation gate before claiming success\u003c/h3\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003eAlways run:\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003e\u003cpre style=\"background:#0a0a1c;border:1px solid #1e1e3f;border-radius:6px;padding:10px 12px;overflow-x:auto;font-size:.9em;margin:8px 0\"\u003e\u003ccode style=\"color:#a5f3fc;background:none;padding:0;font-size:1em\"\u003evideo-skill --help\n\u003c/code\u003e\u003c/pre\u003e\u003c/p\u003e\u003cp style=\"margin:8px 0\"\u003eUse \u003ccode style=\"background:#0d0d1e;color:#a5f3fc;padding:1px 5px;border-radius:3px;font-size:.88em\"\u003emake verify\u003c/code\u003e only when working from the source repo.\n\u003c/p\u003e"])</script><script>self.__next_f.push([1,"20:[\"$\",\"div\",null,{\"className\":\"skill-page\",\"children\":[[\"$\",\"script\",null,{\"type\":\"application/ld+json\",\"dangerouslySetInnerHTML\":{\"__html\":\"{\\\"@context\\\":\\\"https://schema.org\\\",\\\"@type\\\":\\\"SoftwareApplication\\\",\\\"name\\\":\\\"Video Skill\\\",\\\"description\\\":\\\"Run the video-skill pipeline to convert narrated videos into structured step data and enriched timeline-ready outputs. 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