# spec-editor

> spec-editor — spec-editor-spec-editor. Use this tool when you need to generate structured specifications from requirements documents, leveraging AI-driven debates to produce accurate and implementable specs in multiple programming languages. It solves the problem of manual spec writing, reducing errors and inconsistencies, and integrates with git for version control. Input your requirements docs and receive output specs with @implements in 7 languages.

Canonical page: https://skillsregistry.net/skills/spec-editor-spec-editor  
JSON: https://api.skillsregistry.net/v1/skills/spec-editor-spec-editor

## Description

Drop requirements docs → AI agents debate → structured specs with @implements in 7 languages.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** Apache-2.0
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/spec-editor/spec-editor)

## 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": "spec-editor-spec-editor"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/spec-editor-spec-editor` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/spec-editor-spec-editor/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