This repository is the source of specify-cli, the flagship Python CLI of Spec Kit. In production it is a Typer-based developer tool that bootstraps projects for Spec-Driven Development: `specify init` scaffolds a `.specify/` structure, installs shared bash/PowerShell/Python helper scripts, and generates agent command/skill files into 37+ AI coding-tool directories (Claude, Copilot, Codex, Gemini, Cursor, Grok, Qwen, Tabnine, Goose, and more). Beyond scaffolding, the tool manages a layered ecosystem of extensions, presets, bundles, and YAML-defined workflows, plus a self-upgrade path that detects uv/pipx/uvx installations and pulls releases from the GitHub API.
OpenSpec is an AI-native spec-driven development CLI tool that provides a lightweight agreement layer between humans and AI coding assistants. It manages structured 'changes' with proposals, delta specs, designs, and tasks, supporting 30+ AI coding tools (Claude, Cursor, Devin, Copilot, etc.) by generating per-tool skills and slash commands. The CLI features a store system for cross-repo planning, an artifact graph for tracking change progress, shell completion generation, and a validation system. The codebase is well-structured with extensive test coverage, reusable components (artifact graph, markdown parser, command generation adapters, store foundation), and security-conscious patterns (atomic writes, prototype pollution guards). It is actively maintained with a large community (70k+ stars).
CCPM is a structured project management skill for AI agents (Claude Code, Codex, etc.) that enforces a spec-driven development workflow: PRD → Epic → GitHub Issues → Parallel Agents → Shipped Code. The codebase consists of markdown reference documents (plan.md, structure.md, sync.md, execute.md, track.md, conventions.md) and a set of deterministic bash scripts that read project state from .claude/ directory (PRDs, epics, tasks with frontmatter). The system does not contain any runtime code—it is purely a collection of instructions and helper scripts that an AI agent reads and executes. Its architecture is a flat skill structure following the agentskills.io standard, with no external dependencies beyond git, gh CLI, and a GitHub repository. The primary data flows are local file operations (creating/reading/updating markdown files) and GitHub API calls via gh CLI for issue creation, syncing, and closing. The skill is harness-agnostic and works with any compatible agent framework.