From workflows
Extracts reusable patterns from Claude Code sessions and saves them as learned skills for future use. Useful after long sessions with complex problem-solving.
How this skill is triggered — by the user, by Claude, or both
Slash command
/workflows:continuous-learningThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Extract reusable patterns from sessions and save them as learned skills for future use.
Extract reusable patterns from sessions and save them as learned skills for future use.
This skill analyzes the session transcript to identify extractable patterns:
~/.claude/skills/Use /learn command or invoke directly:
/continuous-learning
Edit config.json to customize:
{
“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”
]
}
| 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 |
Extracted skills are saved following the standard skill directory structure:
~/.claude/skills/learned/
├── fix-marimo-import-error/
│ └── SKILL.md
├── debug-pixi-environment/
│ └── SKILL.md
└── wrds-connection-pattern/
└── SKILL.md
Each learned skill follows standard SKILL.md format with:
The skill reads from CLAUDE_TRANSCRIPT_PATH (JSON conversation transcript)
which is automatically set by Claude Code during sessions.
/learn command - Manual pattern extraction mid-session/checkpoint command - Save session statenpx claudepluginhub edwinhu/workflows --plugin workflowsExtracts reusable patterns from Claude Code sessions and saves them as learned skills. Useful for curating personal knowledge from past sessions.
Guides creation, editing, and verification of skills for AI coding agents using test-driven development with subagent scenarios. Use when authoring or debugging skills.