# Commitshow Audit

> Use this tool when you need to evaluate the quality of public GitHub repositories against a standardized rubric, solving problems of code quality assessment and compliance. It analyzes code practices such as database indexing and security policies, and produces a scored report with strengths, concerns, and recommendations in markdown or JSON format. Ideal for use in development workflows, code reviews, and repository audits to ensure high-quality code and identify areas for improvement.

Canonical page: https://skillsregistry.net/skills/commitshow-audit  
JSON: https://api.skillsregistry.net/v1/skills/commitshow-audit

## Description

Commitshow Audit is an MCP server that evaluates public GitHub repositories against the commit.show quality rubric, producing a 0–100 score with a three-axis breakdown, strengths, concerns, rank, and delta. It analyzes code practices including database indexing, API rate limiting, error tracking, and security policies, delivering results in markdown or JSON format.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-01

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/commitshow-audit)
- **Repository:** <https://github.com/commitshow/cli/tree/HEAD/mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "commitshow-audit"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/commitshow-audit` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/commitshow-audit/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt