# agents-md

> Use this tool when you need to manage and generate documentation for AI agents using Markdown, leveraging git for version control and collaboration. It solves problems related to agent documentation, such as consistency and accessibility, by providing a standardized interface for inputting agent information and outputting formatted Markdown files. Ideal for use cases where agent documentation needs to be easily maintained, updated, and shared across teams.

Canonical page: https://skillsregistry.net/skills/nova-3951-agents-md  
JSON: https://api.skillsregistry.net/v1/skills/nova-3951-agents-md

## Trust

- **Trust score (0–1):** 0.74
- **Verification tier:** verified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/NOVA-3951/agents-md)
- **Repository:** <https://github.com/NOVA-3951/AGENTS.MD>

## 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": "nova-3951-agents-md"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nova-3951-agents-md` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nova-3951-agents-md/pull`

---
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