# Kimi Code Review

> Use this tool when you need to improve code quality and receive structured feedback through a collaborative review process. It solves problems related to code optimization, debugging, and architecture by providing alternative perspectives and challenging proposals. The tool accepts code inputs and outputs detailed feedback, making it ideal for use cases where manual or automated code review is necessary.

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

## Description

This server bridges Claude Code with Kimi AI to provide structured code consultation through a challenge-loop protocol. Kimi serves as a read-only skeptic in four configurable roles — skeptic, architect, debugger, or judge — challenging proposals and offering alternative perspectives while Claude retains decision authority. The server supports manual consultation mode for on-demand requests and auto mode for proactive review, with a transparent evidence chain showing which files and searches informed each response.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

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

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/michaelcecil-kimi-code-review)
- **Repository:** <https://github.com/michaelcecil/kimi-mcp-server>

## 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": "michaelcecil-kimi-code-review"
    }
  }
}
```

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