gotalab

Cc Sdd

Name: Cc Sdd
Author: gotalab

Testing community

SOURCE https://github.com/gotalab/cc-sdd

Description

Spec-driven development (SDD) for your team's workflow. Kiro style commands that enforce structured requirements→design→tasks workflow and steering, transforming how you build with AI. Support Claude Code, Codex, Opencode, Cursor, Github Copilot, Gemini CLI and Windsurf.

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

cc-sdd: Long-running spec-driven implementation for AI coding agents

[![npm version](https://img.shields.io/npm/v/cc-sdd?logo=npm)](https://www.npmjs.com/package/cc-sdd?activeTab=readme) [![install size](https://packagephobia.com/badge?p=cc-sdd)](https://packagephobia.com/result?p=cc-sdd) [![license: MIT](https://img.shields.io/badge/license-MIT-green.svg)](./LICENSE)

Package README: English | 日本語 | 繁體中文

Turn approved specs into long-running autonomous implementation

One command installs an agentic SDLC workflow as Agent Skills: discovery, requirements, design, tasks, and autonomous implementation with per-task independent review. Works across 8 AI coding agents, with the same 17-skill set on each.

👻 **Kiro-inspired.** Similar spec-driven, agentic SDLC style as Kiro IDE. Existing Kiro specs remain compatible and portable.

What's new in v3.0

cc-sdd v3.0 is a rework around Agent Skills and long-running autonomous implementation.

/kiro-discovery as the new entry point. Discovery routes new work into one of: extend an existing spec, implement directly with no spec, create one new spec, decompose into multiple specs, or mixed decomposition. It writes brief.md and, when needed, roadmap.md, so you can resume a workstream without re-explaining scope.
/kiro-impl for long-running autonomous implementation. Each task gets a fresh implementer running TDD (RED → GREEN) behind a feature flag, an independent reviewer, and an auto-debug pass that investigates root causes in a clean context when the implementer is blocked or the reviewer rejects twice. Learnings from earlier tasks propagate forward via ## Implementation Notes in tasks.md. 1 task per iteration, safe to re-run after interruption.
**Boundary-first