Automatically refine both input and output in your development workflow: clarify ambiguous feature requests, review completed work against plans, detect blind spots in specs, verify factual claims, and toggle terse communication modes to save tokens.
Interactive brainstorming session to clarify and refine requests through iterative questioning. Use when user mentions unclear requirements, vague ideas, or needs clarification on features. Do NOT use for clear technical specs, implementation details, or when requirements are already well-defined.
Rethink prior work to verify correctness against an agreed plan, classifying findings as deal-breakers, suggestions, or correct, with a confidence score. Use when the user says "challenge this", "rethink your plan", "is this correct", "review my last decision", "challenge my decision", "challenge what you did", "is my decision right", "criticize this", "find flaws", or asks for a critical review of just-completed work. Do NOT use for line-by-line code review against a style guide, implementing features, writing tests, or generating new code.
Toggle terse output mode with intensity levels (lite, full, ultra) so prose drops articles, filler, and pleasantries while code, quoted errors, and security warnings stay verbatim. Also reports real token usage and estimated savings under condense mode for the current session. Use when the user says "condense", "condense output", "be more concise", "shorter answers", "tighten output", "/condense", "/condense full", "/condense ultra", "stop condense", "normal mode", "/condense-stats", "how much have we saved", or "token savings". Do NOT use for editing existing prose, summarizing a long document, or compressing source code (only output style is affected, not content).
Analytical scan of a markdown artifact (idea, user-stories, PRD, spec) to surface blind spots - unstated assumption, missing actor, missing failure mode, ambiguous term, missing acceptance criterion, missing edge case, and missing dependency - emitting a structured shadow report grouped by category and sorted by severity. Use when the user says "find blind spots in this spec", "what's missing in this PRD", "shadow report", "shadow analysis", "scan for gaps", "find what's missing", "spot blind spots", "review for gaps", or asks for an analytical gap scan of a written artifact. Do NOT use for interactive clarification through iterative Q&A (use aidd-refine:01-brainstorm for that), implementing features, writing tests, or reviewing code style.
Verify factual claims in a piece of text against authoritative sources and rewrite it with footnote citations, hedging any claim that cannot be confirmed. Runs a cheapest-first verification cascade (project memory and docs, then codebase inspection, then web lookup) and reports both sources when they disagree. Use when the user says "fact-check this", "verify that claim", "are you sure about that", "is that actually true", "cite your sources", "where did you get that fact", "did you make that up", "double-check the version you gave me", "vérifie cette information", or "es-tu sûr de ça". Do NOT use to auto-guard the AI's own output (this skill only fires on an explicit request), to judge code logic correctness, or to clarify vague requirements through iterative Q&A - use `aidd-refine:01-brainstorm` for that.
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6 plugins · 37 skills · 3 agents · MIT
Quick start → · Browse plugins → · How it works → · Join Discord →
The AIDD Framework is a marketplace of skills, agents, rules, and conventions that make the AI-Driven Development flow concrete inside your AI coding assistant - the full SDLC (plan → implement → review → ship) under rigorous human supervision. It is the open toolset of the AI-Driven Dev community.
The framework is authored for Claude Code, and this repository is its native marketplace. Every release also attaches archives adapted to each tool we support - Cursor, GitHub Copilot, Codex, OpenCode (marketplace or flat format per tool) - so you grab the build that matches your assistant. See Another AI tool? for the per-tool download + install table.
Founded by Alex Soyes - Blog · GitHub · LinkedIn · X.
Join the conversation: Discord · YouTube · LinkedIn · Website
Just an AI coding assistant. Everything else is per-plugin and optional.
| To… | You need |
|---|---|
| Register & run the marketplace | An AI assistant - Claude Code runs this marketplace natively; for another tool, grab the release archive the aidd-cli builds for it |
| Use a plugin's extras | Only what that plugin's README lists - e.g. gh / glab for VCS, a ticketing tool for PM |
Nothing beyond the AI tool is required just to register the marketplace.
Register the marketplace and install the core plugins (Claude Code slash commands, not shell):
/plugin marketplace add ai-driven-dev/framework
/plugin install aidd-context@aidd-framework
/plugin install aidd-refine@aidd-framework
/plugin install aidd-dev@aidd-framework
/plugin install aidd-vcs@aidd-framework
Then set up project context (guided onboard, or direct project-init) and run the dev flow:
---
title: AIDD quick start
---
flowchart TD
Install["Marketplace + plugins installed"]
Setup{"Set up context"}
Onboard["aidd-context:00-onboard - guided hub"]
Init["aidd-context:02-project-init - context engineering"]
Brainstorm["aidd-refine:01-brainstorm"]
Plan["aidd-dev:01-plan"]
Implement["aidd-dev:02-implement"]
Assert["aidd-dev:03-assert"]
Review["aidd-dev:05-review"]
Commit["aidd-vcs:01-commit"]
PR["aidd-vcs:02-pull-request"]
Learn["aidd-context:10-learn"]
Install --> Setup
Setup -->|guided| Onboard
Setup -->|direct| Init
Onboard --> Init
Init --> Brainstorm
Brainstorm --> Plan
Plan --> Implement
Implement --> Assert
Assert --> Review
Review --> Commit
Commit --> PR
PR --> Learn
/aidd-context:00-onboard - it inspects the project and guides you./aidd-dev:00-sdlc runs plan → implement → review → ship./plugin Discover tab.Knowledge production: project bootstrap, project init, generation of context artifacts (skills, agents, rules, commands, hooks), mermaid diagrams, learn, discovery
Code transformation: Dev SDLC orchestrator (code-shipping pipeline), plan, assert, audit, review, test, refactor, debug, for-sure. Hosts engineering agents.
Orchestration plugin. v1 use case: async development - turn ready issues into pull requests, then iterate on review feedback until a human takes over. Designed to host more orchestration use cases (refactoring, docs, audits) in future versions.
Product management: ticket-info, user-stories-create, prd, spec
External artifacts: commit, pull-request, release-tag, issue-create
npx claudepluginhub ai-driven-dev/framework --plugin aidd-refineUltra-compressed communication mode. Cuts ~75% of tokens while keeping full technical accuracy by speaking like a caveman.
Memory compression system for Claude Code - persist context across sessions
Multi-model consensus engine integrating OpenAI Codex CLI, Gemini CLI, and Claude CLI for collaborative code review and problem-solving.
Curate auto-memory, promote learnings to CLAUDE.md and rules, extract proven patterns into reusable skills.