Mode d’emploi
- Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
- Consultez le document original pour les outils, identifiants et environnements requis.
- Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/oxbshw/watch-skill --skill recovering-from-errorsAvant de commencer
- L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
- Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.
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
watch-skill doctor --jsonRead 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_KEYlocally; - provider model not found: run
watch-skill setup-visionwith 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.
