asking-with-evidence
The user asks a question about a video that was already watched or indexed — "what did they say about X", "what error code…
The user corrected an answer about a video — "no, it actually says X", "that's the wrong timestamp", "you misread the error code" — or asks why a video answer was wrong. Use this to record the correction as a lesson so future answers on similar questions improve, and to show
$ npx -y skills add oxbshw/watch-skill --skill learning-from-mistakes --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/learning-from-mistakesContext preview
The summary Claude sees to decide when to auto-load this skill.
The user corrected an answer about a video — "no, it actually says X", "that's the wrong timestamp", "you misread the error code" — or asks why a video answer was wrong. Use this to record the correction as a lesson so future answers on similar questions improve, and to show
name: learning-from-mistakes version: "1.4.3" description: The user corrected an answer about a video — "no, it actually says X", "that's the wrong timestamp", "you misread the error code" — or asks why a video answer was wrong. Use this to record the correction as a lesson so future answers on similar questions improve, and to show what the system has learned and saved. license: MIT user-invocable: true allowed-tools: Bash, Read
When a video answer turns out wrong, the correction is worth more than an apology. Report it and Watch Skill learns locally — the mistake is classified, stored as a lesson, injected into future similar questions, and where possible the original question is immediately re-asked to confirm the lesson actually fixes it.
The moment the user corrects a video answer, run:
watch-skill lessons add <video_id> "<question>" "<the wrong answer>" "<the correction>"
The output includes the lesson (`error_class`, `guidance`) and, when the question was re-asked, whether the corrected answer now comes back — tell the user which it was. Nothing is uploaded; lessons live in `~/.watch-skill/`.
watch-skill lessons list
watch-skill stats
Lifetime token economics: what text-first answering and the semantic cache have saved versus stuffing raw frames into context. Quote real numbers from it when the user asks whether any of this is worth it.
Give AI agents eyes, ears, and verifiable results. Watch Skill turns video, audio and screen activity into searchable, timestamped evidence, and answers did that actually work? with a deterministic contract rather than a model's opinion.
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The user wants structure pulled out of a watched video — "make chapters for this video", "where does the bug appear in this…
A Watch Skill command failed, video download broke, ffmpeg or yt-dlp is missing, a provider returned an error, local vision…
The user wants to share or hand off what was found in a video — "send this analysis to my team", "make a page I can share",…