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.
git clone --depth 1 https://github.com/multiplex-ai/muggle-ai-teamsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/multiplex-ai/muggle-ai-teams/skill-create)<a href="https://agentmods.dev/commands/multiplex-ai/muggle-ai-teams/skill-create"><img src="https://agentmods.dev/badge/commands/multiplex-ai/muggle-ai-teams/skill-create/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/multiplex-ai/muggle-ai-teams/skill-create"><img src="https://agentmods.dev/badge/commands/multiplex-ai/muggle-ai-teams/skill-create.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00028 | $0.01143 |
| Opus 5.5 | $0.00011 | $0.00457 |
| Sonnet 5.5 | $0.00006 | $0.00229 |
| Haiku 4.5 | $0.00003 | $0.00114 |
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 6d 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.
This is a copy
95% identical to skill-create — 2 lines 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.
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
- Parses Git History - Analyzes commits, file changes, and patterns
- Detects Patterns - Identifies recurring workflows and conventions
- Generates SKILL.md - Creates valid Claude Code skill files
- 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}
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.
- 6d ago First seen · 175 lines · 28 tokens per session scan A 3acec769ffb3
skill-create is a command published in the GitHub repository multiplex-ai/muggle-ai-teams (2 stars, last pushed 2d ago), licensed MIT. It adds 28 tokens to every session and 1,143 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to skill-create, differing in 2 lines, and is treated as a copy.
Other commands, from other repositories
plan-execute
Execute a validated plan: worktree isolation, TDD scaffolding, level-based parallel agents, quality gate with smoke test, PR creation and merge. Handles everything through to merged PR.
catchup
Restore context after /clear by summarizing recent work and project state.
guardian
Revisión de código IA como pre-commit hook — Guardian Angel.
changelog
Automatic changelog generation. Produces a structured changelog from commit history.
conv-commit
Conventional commit helper command. Reads staged files, suggests type/scope/message, and validates.
commit
Commit current changes following project commit rules (template, body settings).