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Found 2,467 Skills
Agent definition conventions. Use when creating or modifying agents at any level (~/.claude/agents/, .claude/agents/, or project-local). Validate frontmatter, update README.md index. NOT for creating skills, MCP servers, or modifying CLAUDE.md.
Enables continuous self-improvement through learning from failures, user corrections, and capability gaps. Integrates with QAVR for learned memory ranking.
Documentation-driven development specification that requires Agent to consult official documentation and examples before generating code or fixing bugs, including API verification processes, search strategies and MCP invocation rules. It is applicable to scenarios such as accessing third-party libraries, troubleshooting API errors, and version changes.
Engineering operating model for teams where AI agents generate a large share of implementation output.
Orchestration workflow for orchestrator role ONLY. Use when: - Agent's role name (tmux pane title) is "orchestrator"
Strategic planning with optional interview workflow
Orchestrate the full ToolUniverse self-improvement cycle: discover APIs, create tools, test with researcher personas, fix issues, optimize skills, and push via git. References and dispatches to all other devtu skills. Use when asked to: run the self-improvement loop, do a debug/test round, expand tool coverage, improve tool quality, or evolve ToolUniverse.
Probes CLI agents (Codex, Gemini) and writes docs/environment_state.json — agent availability config for Phase 0
Modern TypeScript patterns your AI agent should use. Strict mode, discriminated unions, satisfies operator, const assertions, and type-safe patterns for TypeScript 5.x.
Technical guide for creating a new Paperclip agent adapter. Use when building a new adapter package, adding support for a new AI coding tool (e.g. a new CLI agent, API-based agent, or custom process), or when modifying the adapter system. Covers the required interfaces, module structure, registration points, and conventions derived from the existing claude-local and codex-local adapters.
AI creative director that turns a user's natural-language idea into a complete storyboard and generates all assets — images, video clips, and audio — automatically. The user only describes what they want; all prompt engineering is handled internally.
Patterns for building AI agents that learn from their own execution, detect failure modes, and improve autonomously. Covers feedback loops, performance regression detection, memory curation, skill extraction, and meta-learning architectures. Use when building agents that need to get better over time, managing auto-memory, or designing self-correcting systems.