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Found 776 Skills
Generate and improve prompts using best practices for OpenAI GPT-5 and other LLMs. Apply advanced techniques like chain-of-thought, few-shot prompting, and progressive disclosure.
One-click initialization of a multi-agent repository from the Antigravity template. Use this skill when users want to scaffold a new project quickly (`quick` mode) or with runtime defaults (`full` mode) including LLM provider profile, MCP toggle, swarm preference context, sandbox type, and optional git init.
Integrate Databuddy analytics into applications using the SDK or REST API. Use when implementing analytics tracking, feature flags, custom events, Web Vitals, error tracking, LLM observability, or querying analytics data programmatically.
Add or refresh a fixed 20-line file-header comment that summarizes a source file and indexes key classes/functions with line-number addresses. Use when annotating large codebases for fast navigation, onboarding, refactors, or when you want LLMs/humans to locate relevant symbols quickly without reading entire files.
AI and ML expert including PyTorch, LangChain, LLM integration, and scientific computing
Data engineering, machine learning, AI, and MLOps. From data pipelines to production ML systems and LLM applications.
Optimizes markdown documents for token efficiency, clarity, and LLM consumption. Use when (1) a markdown file needs streamlining for use as LLM context, (2) reducing token count in documentation without losing meaning, (3) converting verbose docs into concise reference material, (4) improving structure and scannability of markdown files, or (5) preparing best-practices or knowledge docs for agent consumption.
Consult external LLMs (Gemini, OpenAI/Codex, Qwen) for second opinions, alternative plans, independent reviews, or delegated tasks. Use when a user asks for another model's perspective, wants to compare answers, or requests delegating a subtask to Gemini/Codex/Qwen.
Validate changesets in openai-agents-js using LLM judgment against git diffs (including uncommitted local changes). Use when packages/ or .changeset/ are modified, or when verifying PR changeset compliance and bump level.
Hub skill for requirements elicitation. Provides technique selection, orchestration guidance, LLMREI patterns, and autonomy level configuration. Use when gathering requirements from stakeholders, conducting elicitation sessions, or preparing requirements for specification.
Motto: The LLM is the dice. It narrates the outcome.
Optimize LLM prompts, tools, and agents in Opik using standardized optimizer workflows (prompt optimization, tool optimization, and parameter tuning), dataset/metric wiring, and result interpretation.