writing-agents
A framework for creating, testing, and managing autonomous AI subagents within project environments using Test-Driven Development principles.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
478 skills found
A framework for creating, testing, and managing autonomous AI subagents within project environments using Test-Driven Development principles.
Systematic project technology stack detection, framework-specific skill auto-loading, and multi-stack analysis for fullstack projects like React + Go.
Create, test, and validate custom Semgrep rules for security vulnerabilities and code pattern detection.
Implement the 'Engineering as Marketing' growth strategy: build free SEO-driven utility tools to drive organic traffic, capture leads, and convert visitors into customers without ad spend.
Explains complex concepts using master teaching frameworks like Feynman, Socratic, and Cognitive Load theory to ensure deep, clear understanding.
Provides predefined design system references for UI reviews, including Material Design 3, Apple HIG, Tailwind UI, Ant Design, and Shadcn/ui.
A deep reasoning protocol that ensures systematic analysis, multi-hypothesis generation, and rigorous verification for complex architectural, debugging, and high-stakes tasks.
A specification-driven workflow management system for structured development lifecycle management, covering proposal, planning, implementation, and archival phases.
Advanced context engineering system for orchestrating AI agents, memory management, and token optimization to improve long-term persistence and project intelligence.
Master professional TDD with the London (mockist) and Chicago (classicist) schools. Automate test-first workflows, style selection, and refactoring with AI agents.
CLI tools for Svelte 5 documentation lookup and code analysis. Automate Svelte component creation, debugging, and linting with real-time documentation retrieval and code autofixing.
Automates the triage, prioritization, and feedback process for new MultiQC module requests by analyzing repository activity, community engagement, and technical feasibility.