# Specky

> Specky — paulasilvatech-specky. Use this tool when you need to streamline Spec-Driven Development by automating the transformation of natural language ideas into structured specifications. It solves problems of manual specification writing, inconsistent requirements, and lengthy project setup by generating production-grade artifacts like requirements and task lists. Input meeting transcripts or ideas, and Specky outputs structured project artifacts in EARS notation, saving time and reducing errors in the development process.

Canonical page: https://skillsregistry.net/skills/paulasilvatech-specky  
JSON: https://api.skillsregistry.net/v1/skills/paulasilvatech-specky

## Description

An MCP server for Spec-Driven Development that transforms natural language ideas and meeting transcripts into structured, production-grade specifications using EARS notation. It automates a 7-phase pipeline to generate project artifacts like requirements, architecture designs, and task lists directly to disk.

## Trust

- **Trust score (0–1):** 0.77
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/uvdtluqulk)
- **Repository:** <https://github.com/paulasilvatech/specky>

## 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": "paulasilvatech-specky"
    }
  }
}
```

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