AIDD structures your AI coding assistant with skills, agents, rules, and a memory bank so it produces consistent, high-quality work, regardless of which AI tool you use (Claude Code, Cursor, Copilot, Codex, OpenCode).

• What You Get
  • Concepts
  • Plugins
  • Framework Structure
  • Memory Block Lifecycle
• Installation
• Typical Workflow
• Optional: Async Automation
• Validation Rules
• References

A plugin marketplace of skills, agents, rules, templates, and a memory system. You invoke skills through your AI tool (slash command, MCP, or natural language trigger) and the AI follows structured workflows instead of guessing.

Skills are grouped into plugins by domain. Install only the plugins you need.

See the CATALOG for the exhaustive list of skills and actions.

AIDD installs alongside your code. Each AI tool's configuration directory holds the skills, agents, and rules it can load. Shared docs and memory live under aidd_docs/.

my-project/
├── .claude/                     # Claude Code: skills, agents, rules, hooks
├── .cursor/                     # Cursor: skills, agents, rules
├── .github/copilot-instructions.md   # GitHub Copilot
├── AGENTS.md                    # Cursor, Codex, OpenCode (shared)
├── CLAUDE.md                    # Claude Code
├── aidd_docs/
│   ├── memory/                  # Project context (loaded each conversation)
│   │   ├── internal/            #   AIDD workflow traces (learn captures, audit notes)
│   │   ├── external/            #   External documentation references
│   │   ├── architecture.md
│   │   ├── codebase-map.md
│   │   ├── coding-assertions.md
│   │   ├── deployment.md
│   │   ├── project-brief.md
│   │   ├── testing.md
│   │   └── vcs.md
│   ├── internal/
│   │   └── decisions/           # Decision records written by aidd-context:10-learn
│   ├── tasks/                   # Specs, plans, run summaries
│   ├── ADR.md                   # Architecture decision log (aidd-context:10-learn)
│   ├── README.md                # This file
│   ├── GUIDELINES.md            # Developer operating guidelines
│   └── CONTRIBUTING.md          # How to add or modify skills, agents, rules
├── src/                         # Your application code
└── tests/

Each AI context file (CLAUDE.md, AGENTS.md, .github/copilot-instructions.md, etc.) contains an <aidd_project_memory> block. It is:

1. Seeded the first time by aidd-context:02-project-memory (the skill creates the block if absent).
2. Kept in sync automatically by a session-start hook (aidd-context/hooks/update_memory.js) that scans aidd_docs/memory/ and writes the current list of .md files into the block.

You never edit the block by hand. To change what the AI sees, add or remove files under aidd_docs/memory/; the hook picks them up at the next session.

AIDD is delivered as a plugin marketplace. Pick what you need; do not install everything.

• Remote marketplace (default): add the AIDD marketplace via your AI tool's plugin manager, then install only the plugins your project actually uses (e.g. aidd-context + aidd-dev + aidd-vcs).
• Local marketplace: clone the AIDD framework repo and point your AI tool's plugin manager at the local folder. Useful for offline work, custom forks, or contributing to the framework.

Each plugin is independently installable; install incrementally. Smaller surface, fewer triggers competing.

A typical change cycles through skills from several plugins. The order below is indicative; skip what you do not need and loop back as the work demands.

1. Bootstrap (only for a brand-new project): aidd-context:01-bootstrap imagines the stack and architecture, comparing candidate stacks and writing an INSTALL.md. Skip this step on an existing project.
2. Project init (once per project, re-runnable to refresh): aidd-context:02-project-memory scaffolds aidd_docs/, the memory bank, and the AI context files for the tools you use. Re-running later refreshes the scaffold without overwriting your customizations.
3. Frame the request: aidd-refine:01-brainstorm to clarify, aidd-pm:01-ticket-info to pull tracker data, aidd-pm:02-user-stories-create and aidd-pm:03-prd or aidd-pm:04-spec to formalize scope.
4. Plan: aidd-dev:01-plan produces the technical plan, component behavior model, or design-image extraction.
5. Implement and assert: aidd-dev:02-implement writes code against the plan; aidd-dev:03-assert verifies the result.
6. Review: aidd-dev:05-review for code and functional review; aidd-refine:02-challenge to stress-test the result.
7. Test: aidd-dev:06-test adds or runs tests and validates user journeys.
8. Document and learn: aidd-context:09-mermaid for diagrams; aidd-context:10-learn to feed insights back into the memory bank or rules.
9. Ship: aidd-vcs:01-commit, aidd-vcs:02-pull-request, then aidd-vcs:03-release-tag when the work is in production. File issues with aidd-vcs:04-issue-create.
10. Refactor and maintain: aidd-dev:07-refactor for performance or security, aidd-dev:04-audit for technical-debt sweeps, aidd-dev:08-debug to reproduce and fix bugs.

When you want the whole synchronous pipeline run in one go (spec, plan, implementation, finalize), invoke aidd-dev:00-sdlc.

Beyond the synchronous path above, aidd-orchestrator runs the SDLC asynchronously on labeled issues (webhook or cron). This is extra: most projects do not need it. Use only when you want the AI to pick up to-implement issues without a human pressing a key.

Inside the synchronous path, aidd-dev:00-sdlc is the Dev SDLC orchestrator that drives spec, plan, implementation, finalize in one go when you want the whole pipeline at once.

• Skills must have an ## Available actions table, ## Default flow, ## Transversal rules.
• Actions must contain only ## Inputs, ## Outputs, ## Process, ## Test.
• Tests must be observable: command, artifact check, or side effect.

See CONTRIBUTING.md for adding or modifying skills, agents, and rules.

External:

• Anthropic, Prompt engineering overview: https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview
• Anthropic, Claude Code memory: https://docs.claude.com/en/docs/claude-code/memory
• OpenAI, Prompt engineering best practices: https://help.openai.com/en/articles/6654000-best-practices-for-prompting
• GitHub Docs, Repository custom instructions for Copilot: https://docs.github.com/en/copilot/how-tos/configure-custom-instructions/adding-repository-custom-instructions-for-github-copilot