# AI Code Review

> Use this tool when you need to analyze and improve code quality across multiple programming languages, solving problems such as detecting hardcoded credentials, measuring complexity, and identifying errors. It provides inputs including code files, git changes, and entire projects, and outputs quality scores, metrics, and issue reports. Use it in development contexts to ensure high-quality code and catch potential issues before deployment.

Canonical page: https://skillsregistry.net/skills/alanniew-code-review  
JSON: https://api.skillsregistry.net/v1/skills/alanniew-code-review

## Description

Provides AI coding assistants with local static analysis capabilities across Python, JavaScript, TypeScript, Java, Go, Rust, C++, and other languages. Exposes three tools: `analyze_file` for per-file quality scoring, complexity metrics, and line statistics; `review_diff` for inspecting uncommitted git changes and detecting issues like hardcoded credentials; and `check_project` for whole-codebase quality overviews. Python files receive AST-based analysis; other languages receive general quality checks. Grades range from A to D based on weighted scoring of errors, warnings, and informational findings.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** version-control
- **Updated:** 2026-09-03

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/alanniew-code-review)
- **Repository:** <https://github.com/alanniew/code-review-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": "alanniew-code-review"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alanniew-code-review` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alanniew-code-review/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