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learning-from-mistakes — Claude Code skill: make the agent learn

Turns your corrections of video answers into stored lessons, so later answers on similar questions get better. Also shows what has been saved.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add oxbshw/watch-skill --skill learning-from-mistakes -a claude-code
Open on GitHub

What learning-from-mistakes does

The skill fires the moment you correct an answer about a video: wrong timestamp, misread error code, a quote that says something else. Instead of an apology, the correction goes into local storage via watch-skill lessons add <video_id> "<question>" "<the wrong answer>" "<the correction>". You get back an error class and guidance for next time.

Where possible the original question is re-asked right after the lesson is written. That tells you whether the corrected answer comes back, and the agent reports which it was. Nothing is uploaded — lessons live in ~/.watch-skill/.

Run watch-skill lessons list to see what has accumulated. watch-skill stats reports lifetime token economics: what text-first answering and the semantic cache saved against stuffing raw frames into context. Only Bash and Read are allowed, so everything goes through the local CLI.

What it helps with

  • capture a correction as a lesson instead of losing it in the chat
  • check whether an answer improves after a lesson is recorded
  • list every lesson saved so far
  • see token savings from text-first answering and the cache

Example prompts for the agent

  • I corrected that answer — wrong timestamp, save it as a lesson
  • show me what you've learned about this video
  • how many tokens did text-first answering save? show me the stats

How to install learning-from-mistakes

1Skills CLI (Vercel)

npx skills add oxbshw/watch-skill --skill learning-from-mistakes -a claude-code

2Manually: put the files in place

~/.claude/skills/learning-from-mistakes/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/learning-from-mistakes/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about learning-from-mistakes

How do I install learning-from-mistakes in Claude?

Run npx skills add oxbshw/watch-skill --skill learning-from-mistakes -a claude-code. The skill lands at ~/.claude/skills/learning-from-mistakes/SKILL.md.

What does learning-from-mistakes do?

It classifies your correction of a video answer, stores it as a lesson, and injects it into similar questions. When it can, it re-asks the original question and tells you whether the lesson fixed the answer.

Where are the lessons stored?

In ~/.watch-skill/ on your machine. Nothing leaves it.

Source text

SKILL.md · MIT
---
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
---

# 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:

```bash
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 what has been learned

```bash
watch-skill lessons list
```

## The savings meter

```bash
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.

© oxbshw · MIT · oxbshw/watch-skill

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