# Optibot

> Use this tool when you need to ensure the quality and reliability of your AI assistant's code, as Optibot provides AI-powered code review for local changes, branch diffs, and patch files, helping to identify and fix errors, and improve overall performance. It solves problems related to code quality, consistency, and maintainability, and accepts code files and repositories as input, producing detailed review reports as output. Optibot is ideal for use during AI model development, deployment, and maintenance phases.

Canonical page: https://skillsregistry.net/skills/ai-getoptimal-optibot  
JSON: https://api.skillsregistry.net/v1/skills/ai-getoptimal-optibot

## Description

AI code review for your AI assistant — review local changes, branch diffs, and patch files.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.4.1
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-06-12

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.getoptimal%2Foptibot)

## 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": "ai-getoptimal-optibot"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-getoptimal-optibot` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-getoptimal-optibot/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