continuous-learning
Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.
Skill by vibeeval
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/vibeeval-continuous-learning
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: agent-building
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Shell scripts
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/continuous-learning
What's inside
- Skill name
continuous-learning- Description
- Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.
- License
- MIT
- Instructions
- 107 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (3)
- SKILL.md
- config.json
- evaluate-session.sh
SKILL.md (first lines)
---
name: continuous-learning
description: Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.
---
# Continuous Learning Skill
Automatically evaluates Claude Code sessions on end to extract reusable patterns that can be saved as learned skills.
## How It Works
This skill runs as a **Stop hook** at the end of each session:
1. **Session Evaluation**: Checks if session has enough messages (default: 10+)
2. **Pattern Detection**: Identifies extractable patterns from the session
3. **Skill Extraction**: Saves useful patterns to `~/.claude/skills/learned/`
## Configuration
Edit `config.json` to customize:
```json
{
"min_session_length": 10,
"extraction_threshold": "medium",
"auto_approve": false,
"learned_skills_path": "~/.claude/skills/learned/",
"patterns_to_detect": [
"error_resolution",
"user_corrections",
"workarounds",
"debugging_techniques",
"project_specific"
],
"ignore_patterns": [
"simple_typos",
"one_time_fixes",
"external_api_issues"
]
}
```
## Pattern Types
| Pattern | Description |
|---------|-------------|
| `error_resolution` | How specific errors were resolved |
| `user_corrections` | Patterns from user corrections |
| `workarounds` | Solutions to framework/library quirks |
| `debugging_techniques` | Effective debugging approaches |
| `project_specific` | Project-specific conventions |
## Hook Setup
Add to your `~/.claude/settings.json`:
```json
{
"hooks": {
"Stop": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "~/.claude/skills/continuous-learning/evaluate-session.sh"
}]
}]
}
}
```
## Why Stop Hook?
- **Lightweight**: Runs once at session end
- **Non-blocking**: Doesn't add latency to every message
- **Complete context**: Has access to full session transcript
## Related
- [The Longform Guide](https://x.com/affaanmustafa/status/2014040193557471352) - Section on continuous learning
- `/learn` command - Manual pattern extraction mid-session
---
## Comparison Notes (Research: Jan 2025)
### vs Homunculus (github.com/humanplane/homunculus)
Homunculus v2 takes a more sophisticated approach:
| Feature | Our Approach | Homunculus v2 |
|---------|--------------|---------------|
| Observation | Stop hook (end of session) | PreToolUse/PostToolUse hooks (100% reliable) |
| Analysis | Main context | Background agent (Haiku) |
| Granularity | Full skills | Atomic "instincts" |
| Confidence | None | 0.3-0.9 weighted |
| Evolution | Direct to skill | Instincts → cluster → skill/command/agent |
| Sharing | None | Export/import instincts |
**Key insight from homunculus:**
> "v1 relied on skills to observe. Skills are probabilistic—they fire ~50-80% of the time. v2 uses hooks for observation (100% reliable) and instincts as the atomic unit of learned behavior."
### Potential v2 Enhancements
1. **Instinct-based learning** - Smaller, atomic behaviors with confidence scoring
2. **Background observer** - Haiku agent analyzing in parallel
3. **Confidence decay** - Instincts lose confidence if contradicted
4. **Domain tagging** - code-style, testing, git, debugging, etc.
5. **Evolution path** - Cluster related instincts into skills/commands
See the continuous-learning-v2 spec for full details.From vibeeval/vibecosystem, MIT.
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Signals
- Stars
- 540
- Forks
- 44
- Open issues
- 5
- Last commit (this folder)
- Mar 23, 2026 (7 months ago)
- Last release
- Apr 12, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/vibeeval/vibecosystem
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
continuous-learning skill. Agent Mart. https://agentmart.dev/skills/vibeeval-continuous-learning (last updated 2026-10-24)