Coordinate AI agent teams to implement features via spec-driven TDD: structured specification interviews through RED/GREEN/REFACTOR cycles, automated code review, performance profiling, changelog generation, project dashboards, and environment-aware deployment orchestration with safety gates.
[ADD v0.5.0] Declare absence — get autonomous work plan for the duration
[ADD v0.5.0] Return from absence — get briefing on autonomous work
[ADD v0.5.0] Update project branding — new colors, fonts, tone, audit artifacts
[ADD v0.5.0] View project branding — accent color, palette, drift detection, image gen status
[ADD v0.5.0] Generate or refresh CHANGELOG.md from conventional commits
Executes bash commands
Hook triggers when Bash tool is used
Modifies files
Hook triggers on file write and edit operations
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AI agents write code fast. Without structure, they ship chaos.
ADD is coordinated agent swarms — test-writers, implementers, reviewers, deployers — that ship verified software as a team. Spec-driven. Test-first. Independently verified. Human-validated.
Website · Install · Quick Start · Agent Teams · Human-in-the-Loop · For PMs · Learning
AI code generation has changed how software gets built, but development practices haven't kept up. Developers and agents operate without structure, leading to specification drift, unpredictable quality, lost knowledge, and unclear handoffs.
ADD brings discipline to AI-native development the same way TDD brought discipline to testing.
TDD gave us tests before code. BDD gave us behavior before tests. ADD gives us coordinated agent teams before everything.
ADD is a structured SDLC methodology where AI agents do the development work — writing tests, implementing features, reviewing code, deploying — while humans architect, decide, and verify the user experience. It's not a tool. It's a way of working.
The six principles:
Marketplace (recommended):
claude plugin marketplace add MountainUnicorn/add
claude plugin install add@add-marketplace
Source install:
claude plugin install --source https://github.com/MountainUnicorn/add
Update an existing install:
claude plugin update add@add-marketplace
No runtime dependencies. No build step. ADD is pure markdown and JSON — it runs entirely within Claude Code's plugin system.
/add:init
ADD interviews you about your project (product vision, tech stack, team size, deployment model) and scaffolds the project structure. Takes about 5 minutes.
What gets created:
your-project/
├── .add/
│ ├── config.json # Project configuration
│ ├── learnings.md # Agent knowledge base
│ └── cycles/ # Work cycle tracking
├── docs/
│ ├── prd.md # Product Requirements Document
│ ├── plans/ # Implementation plans
│ └── milestones/ # Milestone tracking
├── specs/ # Feature specifications
└── CLAUDE.md # Project context for Claude
/add:spec "user authentication"
ADD runs a structured interview (6-10 questions, ~5 min) and generates a complete feature specification with acceptance criteria, test cases, data models, and edge cases.
/add:plan specs/user-authentication.md
Transforms the spec into an actionable implementation plan with task breakdown, effort estimation, dependency mapping, and risk assessment.
/add:tdd-cycle specs/user-authentication.md
Executes the full TDD cycle: writes failing tests from the spec (RED), implements minimal code to pass them (GREEN), refactors for quality, then independently verifies everything.
/add:verify
Runs up to 5 levels of quality checks: lint, type checking, unit tests, coverage, and spec compliance. For UI projects, humans validate the user experience via screenshot review.
/add:deploy
Environment-aware deployment with pre-deploy verification and post-deploy smoke tests.
ADD doesn't use a single agent. It dispatches specialized sub-agents — each with scoped tool permissions — then independently verifies their work. Trust but verify.
npx claudepluginhub mountainunicorn/add --plugin addSpecification-driven development workflow: specify → plan → tasks → implement
Spec-driven development for big features. When features get too big, plan mode gets too vague—leading to hallucinations during implementation. ShipSpec replaces vague plans with structured PRDs, technical designs, and ordered tasks that keep Claude grounded.
Spec-driven development using GitHub spec-kit methodology. Constitution-first approach with specify, plan, tasks, and implement phases.
Skills-first specification-driven development framework with 7 agent skills for planning, implementation, review, and shipping. Natural language activation with intelligent agent orchestration. Includes /plan, /implement, /research commands plus managing-specifications, implementing-features, and reviewing-and-shipping skills.
Long-running agent harness with 5-layer memory architecture, GitHub integration, autonomous batch processing, Agent Teams with ATDD, 9 hooks (safety, quality gates, team coordination), and 6 Agent Skills
Helder's personal SDLC toolbelt for AI coding agents — from PRD to ship. Bundles the tracer-bullet workflow alongside TDD, code review, audits, and shipping skills.