skill-create

A command that reads a repository’s Git history—its record of code changes—to find repeated coding patterns and create SKILL.md instruction files.

In plain words
What is it for?
Use it to analyze recent commits, choose how many commits to inspect, save generated skills in a chosen folder, or create additional instincts for a continuous-learning system.
Why use it?
It turns existing team habits into written guidance, so coding agents can follow the project’s conventions without someone documenting them by hand.

Command

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/rohitbind123/claude-setup/skill-create
Clone the repo
git clone --depth 1 https://github.com/RohitBind123/claude-setup
Per session 28 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,143 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00028 $0.01143
Opus 5 $0.00014 $0.00571
Sonnet 5 $0.00006 $0.00229
Haiku 4.5 $0.00003 $0.00114

Measured 2d ago against content hash 3acec769ffb3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

skill-create scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to skill-create — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

commands/skill-create.md · 175 lines

How it starts

The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/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}

Read the full file on GitHub · 175 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 175 lines · 28 tokens per session scan A 3acec769ffb3

Subscribe to this mod's changes

skill-create is a command published in the GitHub repository RohitBind123/claude-setup (2 stars, last pushed 4mo ago), licensed MIT. It adds 28 tokens to every session and 1,143 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to skill-create, differing in 1 line, and is treated as a copy.