Learn

pedrohcgs/learn

| 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.

1k tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

1440

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/pedrohcgs/claude-code-my-workflow --skill learn

The instruction itself

9 sections, as written by the author

/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:

"What did I just learn that wasn't obvious before starting?"
"Would future-me benefit from this being documented?"
"Was the solution non-obvious from documentation alone?"
"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:

# 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 the skill file at .claude/skills/[skill-name]/SKILL.md:

---
name: descriptive-kebab-case-name
description: |
  [CRITICAL: Include specific triggers in the description]
  - What the skill does
  - Specific trigger conditions (exact error messages, symptoms)
  - When to use it (contexts, scenarios)
author: Claude Code Academic Workflow
version: 1.0.0
argument-hint: "[expected arguments]"  # Optional
---

# Skill Name

## Problem
[Clear problem description — what situation triggers this skill]

## Context / Trigger Conditions
[When to use — exact error messages, symptoms, scenarios]
[Be specific enough that you'd recognize it again]

## Solution
[Step-by-step solution]
[Include commands, code snippets, or workflows]

## Verification
[How to verify it worked]
[Expected output or state]

## Example
[Concrete example of the skill in action]

## References
[Documentation links, related files, or prior discussions]

PHASE 4: Quality Gates

Before finalizing, verify:

[ ] Description has specific trigger conditions (not vague)
[ ] Solution was verified to work (tested)
[ ] Content is specific enough to be actionable
[ ] Content is general enough to be reusable
[ ] No sensitive information (credentials, personal data)
[ ] Skill name is descriptive and uses kebab-case

Output

After creating the skill, report:

✓ Skill created: .claude/skills/[name]/SKILL.md
  Trigger: [when to use]
  Problem: [what it solves]

Example: Creating a Skill

User discovers that a specific R package silently drops observations:

---
name: fixest-missing-covariate-handling
description: |
  Handle silent observation dropping in fixest when covariates have missing values.
  Use when: estimates seem wrong, sample size unexpectedly small, or comparing
  results between packages.
author: Claude Code Academic Workflow
version: 1.0.0
---

# fixest Missing Covariate Handling

## Problem
The fixest package silently drops observations when covariates have NA values,
which can produce unexpected results when comparing to other packages.

## Context / Trigger Conditions
- Sample size in fixest is smaller than expected
- Results differ from Stata or other R packages
- Model has covariates with potential missing values

## Solution
1. Check for NA patterns before regression:

summary(complete.cases(data[, covariates]))

2. Explicitly handle NA values or use `na.action` parameter
3. Document the expected sample size in comments

## Verification
Compare `nobs(model)` with `nrow(data)` — difference indicates dropped obs.

## References
- fixest documentation on missing values
- [LEARN:r-code] entry in MEMORY.md

How to use it

Copy the folder

Take pedrohcgs/learn from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.