This project is a practical manual and starter kit for running a complete workflow with AI, from product requirements and implementation planning to coding, verification, and code review.
개요
This project is a practical manual and starter kit for running a complete workflow with AI, from product requirements and implementation planning to coding, verification, and code review. It provides a skills-first, reusable structure you can copy into your own repository to operationalize SDD in day-to-day delivery. It is useful because it turns SDD from a high-level idea into a repeatable system with shared standards, canonical prompts, and portable conventions that stay consistent across Codex, Cursor, and Claude. It is highly recommended to use it with a spec-driven process such as OpenSpec. If you want to try our best-practices in an Openspec-ready ecosystem, check out our Openspec AI Specs alternative This repository keeps a single canonical source in ai-specs/ and exposes it to each copilot folder using symlinks: - .codex/* links to canonical resources - .cursor/* links to canonical resources - .
README
AI Specs for Skills-First Development
This project is a practical manual and starter kit for running a complete Spec-Driven Development (SDD) workflow with AI, from product requirements and implementation planning to coding, verification, and code review. It provides a skills-first, reusable structure you can copy into your own repository to operationalize SDD in day-to-day delivery.
It is useful because it turns SDD from a high-level idea into a repeatable system with shared standards, canonical prompts, and portable conventions that stay consistent across Codex, Cursor, and Claude.
It is highly recommended to use it with a spec-driven process such as OpenSpec.
If you want to try our best-practices in an Openspec-ready ecosystem, check out our Openspec AI Specs alternative
Repository Structure
.
├── ai-specs/
│ ├── .agents/ # Canonical agent role definitions
│ ├── .commands/ # Small set of shared utility commands
│ └── skills/ # Canonical skill definitions (main workflow entrypoint)
│
├── .codex/
│ ├── agents -> ../ai-specs/.agents
│ ├── commands -> ../ai-specs/.commands
│ └── skills -> ../ai-specs/skills
│
├── .cursor/
│ ├── agents -> ../ai-specs/.agents
│ ├── commands -> ../ai-specs/.commands
│ ├── skills -> ../ai-specs/skills
│ └── rules/
│
├── .claude/
│ ├── agents -> ../ai-specs/.agents
│ ├── commands -> ../ai-specs/.commands
│ └── skills -> ../ai-specs/skills
│
├── docs/ # Project technical context and reference docs
└── README.md
Multi-Copilot Strategy
This repository keeps a single canonical source in ai-specs/ and exposes it to each copilot folder using symlinks:
.codex/*links to canonical resources.cursor/*links to canonical resources.claude/*links to canonical resources
Why This Approach
- Single source of truth: one canonical definition for agents, commands, and skills
- No duplicated maintenance: update once, all copilot folders stay aligned
- Tool compatibility: each copilot reads from its expected folder structure
- Safe evolution: workflows can change without reorganizing every tool-specific folder
Skills-First Workflow
Use skills as the default entrypoint for recurring tasks.
Current examples in this repository:
ai-specs/skills/enrich-user-story/SKILL.mdai-specs/skills/write-pr-report/SKILL.md
Commands still exist as lightweight utilities in ai-specs/.commands, but the main functional workflows should be implemented as skills.
Technical Context Location
Project-level technical context now belongs in docs/, for example:
docs/doc_architecture.mddocs/doc_ai_planning_mode.mddocs/doc_verification_guide.md
If you bootstrap this setup into another project, replace these documents with your own architecture, planning, and verification references.
Quick Start
- Copy this structure into your project.
- Keep
ai-specs/as canonical. - Create symlinks from
.codex/,.cursor/, and.claude/toai-specs/. - Store project context in
docs/. - Build new reusable workflows as skills under
ai-specs/skills/.
Customization Guidelines
- Update agent definitions in
ai-specs/.agents/. - Add or refine skills in
ai-specs/skills/. - Keep commands minimal and only for utility behavior.
- Keep symlinks relative so the repo stays portable.
- Document project-specific technical context in
docs/.
Contributing
When contributing:
- Prefer creating/updating a skill over adding a new command.
- Keep canonical content inside
ai-specs/. - Preserve symlink-based sharing across copilot folders.
- Keep
docs/aligned with the real project state.
Creator
This framework was created by Javier Vargas, Head of AI @ Mapal.
He is the original author of the approach, structure, and workflow design implemented in this repository.
Connect with him on LinkedIn.
License
Copyright © 2026 LIDR.co
Licensed under the MIT License
This repository is part of the AI4Devs program by LIDR.co. Learn more at LIDR.co.
추천 도구
다른 키워드를 입력하거나 필터를 제거해 보세요.
설치
npx skillfish add lidr-academy/manual-sdd