Claude Code, Codex, and Cursor
Find skills that work in Claude Code, Codex, and Cursor. See what each one does, look at its files, then install it with one command.
20 skills loaded
Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or se...
Published by Orchestra Research
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Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.
Published by Orchestra Research
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Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter se...
Published by Orchestra Research
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Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library
Published by Orchestra Research
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Fine-tunes and evaluates OpenVLA-OFT and OpenVLA-OFT+ policies for robot action generation with continuous action heads, LoRA adaptation, and FiLM conditioning on LIBERO simulation and ALOHA real-world setups. Use when reproducing OpenVL...
Published by Orchestra Research
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High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.
Published by Orchestra Research
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Old v2 (experimental) of taste-skill, the single-file dial-driven version, preserved for projects depending on its exact behavior. The current default is `design-taste-frontend` (v2). Use this install name only if you need the earlier be...
Published by Leon Lin
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Use when creating new skills, editing existing skills, or verifying skills work before deployment
Published by Jesse Vincent
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Use when you have a spec or requirements for a multi-step task, before touching code
Published by Jesse Vincent
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Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
Published by Jesse Vincent
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Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions
Published by Jesse Vincent
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Use when starting feature work that needs isolation from current workspace or before executing implementation plans - ensures an isolated workspace exists via native tools or git worktree fallback
Published by Jesse Vincent
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Use when implementing any feature or bugfix, before writing implementation code
Published by Jesse Vincent
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Use when executing implementation plans with independent tasks in the current session
Published by Jesse Vincent
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Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Published by Jesse Vincent
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Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Published by Jesse Vincent
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Use when implementation is complete, all tests pass, and you need to decide how to integrate the work
Published by Jesse Vincent
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Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
Published by Jesse Vincent
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Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Published by Jesse Vincent
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Use when a superpowers session went wrong and your human partner wants to know why — repeated work, ignored plans, stumbles, poor results, a skill that didn't fire, "it took too long", "why is it so expensive", "what is it doing" — or wa...
Published by Jesse Vincent
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