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Found 3,730 Skills
Git workflow and GitHub collaboration patterns including conventional commits, branch naming, PR workflow, and gh CLI usage. Use when creating commits, branches, or pull requests. TRIGGER when: git commit, branch, PR, pull request, merge, gh cli. DO NOT TRIGGER when: code implementation, testing, documentation without git operations.
Guides edge and tactical autonomous systems—perception-planning-control under latency and safety constraints; behavior trees/state machines vs learned policies; human-on-the-loop; geofencing, no-strike rules, mission abort; sim and field testing; ROS2/middleware patterns; sensor fusion; degraded modes; autonomy audit logging. Use for UAS/autonomous stacks, safety rules, HITL, sim-to-field validation, fail-safe—not LLM products (ai-engineer), LLM red team (ai-redteam), safeguard serving (ml-infrastructure-engineer-safeguards), governance only (ai-risk-governance), MCU firmware without autonomy (embedded-real-time-software-engineer), plant PLC/DCS (control-software-developer), HIL security bench (hardware-in-the-loop-security-tester).
Guides engineering of multi-agent systems—agent roles and specialization, orchestration topologies (supervisor, peer-to-peer, hierarchical, blackboard), task decomposition and routing, inter-agent messaging (A2A-style patterns), shared vs partitioned state, fan-out/fan-in and DAG workflows, synchronization and consensus, conflict resolution, fault tolerance and retries across agents, cost/latency/token budgets, cross-agent observability, testing multi-agent flows, and deployment (queues, durable workflows). Framework-agnostic; high-level LangGraph, Deep Agents, and agenthub—not single-agent loops (agentic-ai-developer), ML training (ai-engineer), strategy-only whiteboard (enterprise-strategist), or PM planning (technical-program-manager). Use for multi-agent system, multi-agent engineer, agent orchestration, supervisor agent, agent topology, fan-out fan-in, agent handoff protocol, multi-agent workflow, agent coordination, blackboard pattern, hierarchical agents, A2A, agent DAG, multi-agent architecture.
Use when selecting, installing, configuring, smoke-testing, documenting, or troubleshooting MCP servers for academic search, arXiv, Semantic Scholar, OpenAlex, Crossref, PubMed, Zotero, Overleaf, Google Scholar, paper metadata, or scholarly source tooling.
Translate an existing Remotion (React-based) video composition into a HyperFrames HTML composition. Use ONLY when the user explicitly asks to port, convert, migrate, translate, or rewrite a Remotion composition as HyperFrames (e.g. "port my Remotion project to HyperFrames"). Do NOT use when (a) authoring a NEW HyperFrames composition (even if A/B-testing a Remotion video); (b) Remotion is mentioned in passing; (c) Remotion code is shared as reference, not for translation; (d) the user wants "the same video as my Remotion one" without explicitly asking to migrate the source — treat as a fresh HyperFrames build. When in doubt, default to the `hyperframes` skill. Detects unsupported patterns (useState, useEffect side effects, async calculateMetadata, third-party React component libraries, `@remotion/lambda`) and recommends the runtime interop escape hatch instead of a lossy translation.
Build a complete agent-readable Obsidian vault for a Tailwind-based web codebase, eight flat top-level domain docs (PRODUCT/RUNTIME/ARCHITECTURE/DATA/AUTH/ENGINEERING/TESTING/DESIGN), folder-level deep specs, bidirectional wikilinks for graph navigation, and a `DESIGN.md` that conforms to the google-labs-code/design.md spec with tokens derived from `tailwind.config.{ts,js}` or the v4 `@theme` block. Use when asked to "set up project docs", "write project documentation", "create an Obsidian vault from this repo", "document this codebase for agents", "add a DESIGN.md", or "make the design system machine-readable".
Quickly creates new Claude Code skills or translates ChatGPT projects into Claude Code skills. Handles skill scaffolding, frontmatter, directory structure, and ChatGPT-to-Claude migration. Use when the user wants to 'create a skill,' 'make a new slash command,' 'convert a ChatGPT project,' 'translate a GPT to Claude,' or 'migrate prompts to Claude Code.' For full eval/testing/benchmarking workflows, use skill-creator instead.
Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing, activation patching, interchange intervention training, or testing causal hypotheses about model behavior.
Expert guidance for unix-goto shell navigation tool development, including architecture, 9-step feature workflow, testing (100% coverage), performance optimization (<100ms targets), and Linear issue integration
Restructures existing code to improve readability, maintainability, and performance without changing external behavior. USE WHEN: Restructuring code without changing behavior, extracting methods/classes, removing duplication, applying design patterns, improving code organization, reducing technical debt. DO NOT USE: For bug fixes (use /debugging), for adding tests (use /testing), for new features (implement directly). TRIGGERS: refactor, restructure, rewrite, clean up, simplify, extract, inline, rename, move, split, merge, decompose, modularize, decouple, technical debt, code smell, DRY, SOLID, improve code, modernize, reorganize.
Story-level quality orchestrator with 4-level Gate (PASS/CONCERNS/FAIL/WAIVED) and Quality Score. Pass 1: code quality -> regression -> manual testing. Pass 2: verify tests/coverage -> calculate NFR scores -> mark Story Done. Use when user requests quality gate for Story or when ln-400 delegates quality check.
Control Chrome browser via CLI for testing, automation, and debugging. Use when the user needs browser automation, screenshots, form filling or page inspection.