learning-from-mistakes
When a video answer goes wrong, report the correction and Watch Skill records it as a lesson stored locally. The system classifies the mistake, injects it into similar future questions, and can re-ask the original question to verify the fix worked. Check what's been learned or review token savings anytime.
Learning from Mistakes lets you report corrections to wrong video answers so Watch Skill stores them as lessons for future improvement.
AI-generated summary based on this skill's SKILL.md
Decision gist · record as of 2026-07-12
Learning from Mistakes lets you report corrections to wrong video answers so Watch Skill stores them as lessons for future improvement. When a video answer goes wrong, report the correction and Watch Skill records it as a lesson stored locally. The system classifies the mistake, injects it into similar future questions, and can re-ask the original question to verify the fix worked. Check what's been learned or review token savings anytime.
Use it when
- Yes.
- learning-from-mistakes lets you review lessons learned from past video answer corrections anytime.
Verify before relying
Read SKILL.md below before installing (1 file). Open directory: indexed for reading, not audited.
Install
oxbshw/watch-skill/learning-from-mistakes · repository language: Python
Open directory. Skills are indexed for reading, not audited. Review a skill's body before installing it.
Frequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
How do I report a wrong video answer in learning-from-mistakes?
learning-from-mistakes lets you report corrections when a video answer is wrong. Simply flag the mistake, and Watch Skill records it as a lesson stored locally. The system classifies what went wrong, injects the correction into similar future questions, and can re-ask your original question to verify the fix actually worked.
Can learning-from-mistakes teach the system when it gets video timestamps wrong?
Yes. learning-from-mistakes is designed to teach the system when it gets video timestamps wrong. Report the error, and the skill stores your correction locally, classifies the mistake type, and uses it to improve responses to similar future video questions about timestamps and related content.
What lessons can I review from past video answer corrections?
learning-from-mistakes lets you review lessons learned from past video answer corrections anytime. You can view all stored corrections, see how the system classified each mistake, and track what improvements were made based on your feedback. This helps you understand patterns in what went wrong.
How does learning-from-mistakes save tokens and improve performance?
learning-from-mistakes understands token and performance savings from cached answers. When corrections are stored and reused for similar questions, the system avoids redundant processing. You can check token savings metrics anytime to see how much efficiency you've gained from your corrections.
Can I verify that a correction fixed the system's video response?
Yes. learning-from-mistakes can re-ask your original question after you've corrected a video answer, letting you verify that the fix actually worked. This confirmation step ensures the lesson was properly learned and will improve future similar questions.
How does learning-from-mistakes improve future video search results?
learning-from-mistakes improves future video search results by teaching from mistakes. When you report errors, the skill stores them locally, classifies the error type, and injects corrections into similar future questions. Over time, this builds a knowledge base that makes video search progressively more accurate.
SKILL.md
Rendered from the published skill. Quoted content, verbatim.
Learning from mistakes
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.
Report a correction
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/.
See
(truncated - see the full file via the links below)
File tree — 1 file
adapters/claude-skill/skills/learning-from-mistakes/SKILL.md
Let your AI agent find skills like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 56,283 agent skills by what they can do, searchable in plain language.
wish › “Report and store a correction when a video answer is wrong”
Give your agent the search over MCP, or paste the wish link into any chat. No install? Search from any chat →
Related skills
Query any video you've already watched to get answers backed by timestamps and confidence scores, drawn from a persistent index rather than re-processing. The skill refuses unclear answers honestly and escalates automatically when uncertain, saving tokens in the process.
Watch Skill processes videos locally by extracting scene-aware frames, running OCR on text within them, and transcribing audio via offline Whisper or captions. It builds a searchable index so follow-up questions are answered without re-processing the video. No API keys required for core features; vision and STT are optional and configurable.
Recovering from Errors guides you through diagnosing Watch Skill failures using the built-in doctor command, which identifies issues with ffmpeg, yt-dlp, video acquisition, provider authentication, and local models. Apply the stated fixes, retry your original operation, and report any persistent structured errors without looping or changing security policies.
Video Memory maintains a searchable index of every video watched on your machine, preserving frames, transcripts, and extracted answers in persistent storage. Search across all indexed videos by keyword or semantic meaning, drill into specific moments, or synthesize answers from insights spanning multiple videos. Batch-import playlists or folders to build your video library quickly.
Watch Skill processes any video—URLs, local files, streams, recordings—by extracting frames, running OCR, and transcribing audio into a unified searchable index. Query the index directly instead of re-watching, and batch-process playlists or folders in one pass.
Pull structured data from videos you've already watched: titled chapters with timestamps for long content, pinpointed bug reports with error frames and OCR text, or opening-hook analysis scored across attention, pacing, visuals, and on-screen text. All answers come straight from the persistent index with no extra model calls.
More skills sharing-results (MIT)