learn

Solid

Extract reusable knowledge from the current session into a persistent skill. Use when you discover something non-obvious, create a workaround, or develop a multi-step workflow that future sessions would benefit from.

AI & Automation 5 stars 1 forks Updated today MIT

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Quality Score: 83/100

Stars 20%
26
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# /learn — Skill Extraction Workflow Extract non-obvious discoveries into reusable skills that persist across sessions. ## When to Use This Skill Invoke `/learn` when you encounter: - **Non-obvious debugging** — Investigation that took significant effort, not in docs - **Misleading errors** — Error message was wrong, found the real cause - **Workarounds** — Found a limitation with a creative solution - **Tool integration** — Undocumented API usage or configuration - **Trial-and-error** — Multiple attempts before success - **Repeatable workflows** — Multi-step task you'd do again - **User-facing automation** — Reports, checks, or processes users will request ## Workflow Phases ### PHASE 1: Evaluate (Self-Assessment) Before creating a skill, answer these questions: 1. "What did I just learn that wasn't obvious before starting?" 2. "Would future-me benefit from this being documented?" 3. "Was the solution non-obvious from documentation alone?" 4. "Is this a multi-step workflow I'd repeat?" **Continue only if YES to at least one question.** ### PHASE 2: Check Existing Skills Search for related skills to avoid duplication: ```bash # Check project skills ls .claude/skills/ 2>/dev/null # Search for keywords grep -r -i "KEYWORD" .claude/skills/ 2>/dev/null ``` **Outcomes:** - Nothing related → Create new skill (continue to Phase 3) - Same trigger & fix → Update existing skill (bump version) - Partial overlap → Update with new variant ### PHASE 3: Create Skill Create t...

Details

Author
alohays
Repository
alohays/paper2pr
Created
5 months ago
Last Updated
today
Language
Python
License
MIT

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