# moxie-docs

> moxie-docs — jackalope-digital-moxie-docs. Use this tool when you need to maintain accurate and up-to-date documentation for your codebase, and want to automate tasks such as fetching conventions, updating affected docs, and identifying outdated or orphaned documents. Moxie Docs enables AI agents to interface with your repos, taking in code changes and outputting updated documentation and convention context. This tool is ideal for ensuring high-quality code output and streamlining documentation management.

Canonical page: https://skillsregistry.net/skills/jackalope-digital-moxie-docs  
JSON: https://api.skillsregistry.net/v1/skills/jackalope-digital-moxie-docs

## Description

Repos indexed with Moxie Docs can use our MCP to let agents fetch codebase conventions, find affected docs from changes, pull outdated docs to update, and identify orphaned docs to keep up to date. Let your agents keep your documentation accurate and updated at all times. Give them better codebase and convention context to improve code output quality.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/jackalope-digital/moxie-docs)

## 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": "jackalope-digital-moxie-docs"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jackalope-digital-moxie-docs` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jackalope-digital-moxie-docs/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