oxbshw/watch-skill

recovering-from-errors

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".

ソースを見る

使い方

  1. インストールコマンドをコピーし、自分の環境へ導入する前にソースを確認します。
  2. 必要なツール、認証情報、対応環境を原文で確認します。
  3. 入力と成果物を指定し、出力を資料と照合します。
npx skills add https://github.com/oxbshw/watch-skill --skill recovering-from-errors

開始前の確認

  • 導入にはモデル契約、API枠、ファイルへのアクセス許可は含まれません。
  • スター数や導入数は活動の指標であり、独立した品質・安全性試験ではありません。
リポジトリの原文

見出し、例、コード、表、リンク、参照画像を含む原文を表示しています。

Recovering from errors

Failures use stable error codes and include an actionable fix. Preserve that evidence; do not replace it with a generic explanation.

Diagnose first

bash
watch-skill doctor --json

Read the failing checks and apply only their stated fixes. doctor can repair managed ffmpeg and yt-dlp binaries, stale locks, corrupt caches, missing frame directories, and known local-model health failures. Re-run it once after remediation.

Retry the original operation once

After doctor is green, repeat the command that failed. If it returns another structured error, report its code, message, and fix. Do not loop indefinitely, silently switch cloud providers, enable cloud STT, or reprocess an already indexed video.

Common routes:

  • acquisition or extractor failure: watch-skill doctor --json, then retry the watch;
  • provider authentication: verify the matching WATCHSKILL_*_API_KEY locally;
  • provider model not found: run watch-skill setup-vision with a valid vision model;
  • low memory or local server failure: reduce the local model/context or select a cloud

provider the user already has;

  • unknown video ID: watch-skill list, then use the listed ID or original source.

Security and cost policy are invariants during recovery. Never upload the video file, enable a paid provider, or raise the cost ceiling merely to make an error disappear.

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oxbshw
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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 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.

導入数
2
GitHub Stars
503
更新日
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configuring-vision

The user wants to connect an LLM or vision provider, already has an API key, asks "can I use OpenAI/Anthropic/Gemini/OpenRouter", wants local Ollama, or needs different cheap and strong models. Use this to configure provider-neutral visual understanding without tying Watch Skill to one agent or model vendor.

導入数
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GitHub Stars
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更新日
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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.

導入数
2
GitHub Stars
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更新日
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learning-from-mistakes

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.

導入数
2
GitHub Stars
503
更新日
10月14日