Total 55,501 skills, AI & Machine Learning has 9232 skills
Showing 12 of 9232 skills
Use this skill when crafting, iterating, or optimizing prompts for LLMs including zero-shot, few-shot, chain-of-thought, role prompting, structured output, and prompt chaining. Not for fine-tuning or training models. Not for evaluating model quality across benchmarks.
Critique-and-rewrite enforcement loop for voice fidelity. Validates generated content against negative prompt checklists and forces revision until it passes. Use when content has been generated in a target voice, voice output feels off, long-form content risks voice drift, or before final delivery of voice content. Use for "validate voice", "check voice", "voice feels wrong", "voice drift", or "rewrite for voice". Do NOT use for initial voice generation, voice profile creation, or content that has no voice target.
Collaborative coding with enforced micro-steps: announce, show diff, wait for confirmation, apply, verify. User controls pace with commands. Works with any domain agent as the executor. Use when: "pair program", "pair with me", "let's code together", "step by step coding", "walk me through implementing", "code with me"
Design and implement autonomous AI marketing agent systems using the PRAL, BDI, and OODA frameworks. Invoke when a client is ready to move beyond reactive GenAI prompting to proactive, autonomous marketing workflows, or when planning an AI-first marketing operations architecture.
Creates well-structured Agent Skills following best practices. Use when building new skills for Claude Code, designing skill directory structures, writing SKILL.md files, or improving existing skills with progressive disclosure patterns.
Mechanize Pattern 15 — the seven-pass adversarial review protocol for academic manuscripts. Spawns 7 forked subagents in parallel (abstract, intro, methods, results, robustness, prose, citations), then synthesizes a prioritized revision checklist. Use for submission-ready or R&R-stage papers where single-pass review isn't enough.
Run structured multi-role design reviews and architecture debates for technical decisions. Use when Codex needs to compare options, pressure-test tradeoffs, recommend an MVP path, or simulate a meeting with distinct evaluation roles such as moderator, skeptic, pragmatist, minimalist, maximalist, retrieval architect, Granary workflow lead, semantic purist, lightweight contrarian, context economist, or workflow conservative.
Get AI-powered match predictions for Premier League and Champions League including scores, next goal, and corners.
DeepSeek integration. Manage Organizations. Use when the user wants to interact with DeepSeek data.
Architecture patterns and best practices for giving AI agents email capabilities. Use when designing how agents send, receive, and manage email conversations, building two-way communication loops, implementing human-in-the-loop approval with drafts, choosing between WebSockets and webhooks, setting up multi-agent email topologies, handling OTP and verification flows, or securing agent email against prompt injection.
Benchmark vLLM or OpenAI-compatible serving endpoints using vllm bench serve. Supports multiple datasets (random, sharegpt, sonnet, HF), backends (openai, openai-chat, vllm-pooling, embeddings), throughput/latency testing with request-rate control, and result saving. Use when benchmarking LLM serving performance, measuring TTFT/TPOT, or load testing inference APIs.
Full optimization workflow, sub-agent launch templates, agent communication contracts, default configurations, tuning strategy, and knowledge base update protocol. Use when: (1) starting an optimization cycle, (2) launching a Profiler or Designer sub-agent, (3) interpreting or formatting agent communication, (4) updating the knowledge base after a profiling or implementation iteration, (5) deciding default configurations or tuning strategy for a kernel.