affaan-m--everything-claude-code/commands/skill-create.md

name, description, allowed_tools

name	description	allowed_tools
skill-create	Analyze local git history to extract coding patterns and generate SKILL.md files. Local version of the Skill Creator GitHub App.	Bash Read Write Grep Glob

/skill-create - Local Skill Generation

Analyze your repository's git history to extract coding patterns and generate SKILL.md files that teach Claude your team's practices.

Usage

/skill-create                    # Analyze current repo
/skill-create --commits 100      # Analyze last 100 commits
/skill-create --output ./skills  # Custom output directory
/skill-create --instincts        # Also generate instincts for continuous-learning-v2

What It Does

1. Parses Git History - Analyzes commits, file changes, and patterns
2. Detects Patterns - Identifies recurring workflows and conventions
3. Generates SKILL.md - Creates valid Claude Code skill files
4. Optionally Creates Instincts - For the continuous-learning-v2 system

Analysis Steps

Step 1: Gather Git Data

# Get recent commits with file changes
git log --oneline -n ${COMMITS:-200} --name-only --pretty=format:"%H|%s|%ad" --date=short

# Get commit frequency by file
git log --oneline -n 200 --name-only | grep -v "^$" | grep -v "^[a-f0-9]" | sort | uniq -c | sort -rn | head -20

# Get commit message patterns
git log --oneline -n 200 | cut -d' ' -f2- | head -50

Step 2: Detect Patterns

Look for these pattern types:

Pattern	Detection Method
Commit conventions	Regex on commit messages (feat:, fix:, chore:)
File co-changes	Files that always change together
Workflow sequences	Repeated file change patterns
Architecture	Folder structure and naming conventions
Testing patterns	Test file locations, naming, coverage

Step 3: Generate SKILL.md

Output format:

---
name: {repo-name}-patterns
description: Coding patterns extracted from {repo-name}
version: 1.0.0
source: local-git-analysis
analyzed_commits: {count}
---

# {Repo Name} Patterns

## Commit Conventions
{detected commit message patterns}

## Code Architecture
{detected folder structure and organization}

## Workflows
{detected repeating file change patterns}

## Testing Patterns
{detected test conventions}

Step 4: Generate Instincts (if --instincts)

For continuous-learning-v2 integration:

---
id: {repo}-commit-convention
trigger: "when writing a commit message"
confidence: 0.8
domain: git
source: local-repo-analysis
---

# Use Conventional Commits

## Action
Prefix commits with: feat:, fix:, chore:, docs:, test:, refactor:

## Evidence
- Analyzed {n} commits
- {percentage}% follow conventional commit format

GitHub App Integration

For advanced features (10k+ commits, team sharing, auto-PRs), use the Skill Creator GitHub App:

• Install: github.com/apps/skill-creator
• Comment /skill-creator analyze on any issue
• Receives PR with generated skills

Related Commands

• /instinct-import - Import generated instincts
• /instinct-status - View learned instincts
• /evolve - Cluster instincts into skills/agents

---

Part of Everything Claude Code