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".

소스 보기

사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/oxbshw/watch-skill --skill recovering-from-errors

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

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.

관련 작업

같은 저장소의 Skills

더 많은 Skills

모든 Skills
oxbshw
커뮤니티

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.

설치 수
2
GitHub Stars
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업데이트
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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.

설치 수
2
GitHub Stars
503
업데이트
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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.

설치 수
2
GitHub Stars
503
업데이트
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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.

설치 수
2
GitHub Stars
503
업데이트
10월 14일