Autonomous multi-agent development framework with spec-driven sprints and convergent iteration
Remove old sprint directories with safety checks and archiving options
Analyze codebase and generate a comprehensive project-map.md overview
Create a new sprint directory with specs.md template
Interactive project onboarding - creates project-goals.md and project-map.md
Run the autonomous multi-agent sprint workflow with spec-driven development
Build Python backend with FastAPI. Implement async patterns, APIs, database...
General-purpose implementation agent. Adapts to any technology stack based...
Set up and maintain CI/CD pipelines. Configure builds, tests, deployments,...
Build Next.js 16 frontend. Server/Client Components, TypeScript,...
(Optional, Next.js only) Monitor Next.js runtime errors and diagnostics...
Execute this skill should be used when the user asks about "spawn request format", "agent reports", "agent coordination", "parallel agents", "report format", "agent communication", or needs to understand how agents coordinate within the sprint sys...
Configure this skill should be used when the user asks about "API contract", "api-contract.md", "shared interface", "TypeScript interfaces", "request response schemas", "endpoint design", or needs guidance on designing contracts that coordinate ba...
Execute this skill should be used when the user asks about "writing specs", "specs.md format", "how to write specifications", "sprint requirements", "testing configuration", "scope definition", or needs guidance on creating effective sprint specif...
Execute this skill should be used when the user asks about "how sprints work", "sprint phases", "iteration workflow", "convergent development", "sprint lifecycle", "when to use sprints", or wants to understand the sprint execution model and its co...
Uses power tools
Uses Bash, Write, or Edit tools
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Build production agent workflows with empirical verification - Complete teaching system with guides, diagrams, and working examples.
→ Start Here: 5-Minute Introduction | → Visual Architecture Map | → System Summary
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Guides (90+ pages) |
Reference Implementation |
What you'll learn: Turn "LLM analyzed my code" into "LLM + script verified with evidence" - The pattern for production-ready agent systems.
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Consult multiple AI coding agents (Gemini, OpenAI, Grok, Perplexity, plus codex, antigravity, and grok CLIs when installed) to get diverse perspectives on coding problems
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Complete developer toolkit for Claude Code
Production-grade engineering skills for AI coding agents — covering the full software development lifecycle from spec to ship.
Intelligent draw.io diagramming plugin with AI-powered diagram generation, multi-platform embedding (GitHub, Confluence, Azure DevOps, Notion, Teams, Harness), conditional formatting, live data binding, and MCP server integration for programmatic diagram creation and management.
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