Total 50,615 skills, AI & Machine Learning has 8484 skills
Showing 12 of 8484 skills
A curated collection of research papers and resources on agentic reasoning for Large Language Models, organized by planning, tool use, search, self-evolution, and multi-agent systems.
Execute codeagent-wrapper for multi-backend AI code tasks. Supports Codex, Claude, Gemini, and OpenCode backends with agent presets, skill injection, file references (@syntax), worktree isolation, parallel execution, and structured output.
Guides privacy research engineering for safeguards—PII and sensitive-data detection research, redaction and de-identification evals, memorization and extraction risk studies, privacy benchmarks and labeled corpora, logging/retention minimization for safety pipelines, and research memos on privacy–utility trade-offs for guardrail systems. Use when measuring PII detector quality, designing privacy eval suites for moderation stacks, studying training-data leakage or prompt logging risk, or recommending privacy mitigations for safeguard models—not for SOC 2/GDPR evidence automation (compliance-engineer), legal DPIA or AI policy (ai-risk-governance), harm/toxicity classifier R&D (ml-research-engineer-safeguards), production inference gateways (ml-infrastructure-engineer-safeguards), or general non-privacy research (ai-researcher).
Search for gyms, yoga studios, swimming pools, and sports facilities using Camino AI's location intelligence with AI-powered ranking.
AI-powered generation of complete trading strategy code. Uses create_strategy and create_prediction_market_strategy to transform requirements into production-ready Python code. Most expensive AI tool ($1.00-$4.50 per generation). Generates complete Jesse framework strategies with entry/exit logic, position sizing, and risk management. Use after exploring data and optionally generating ideas. ALWAYS test with test-trading-strategies before deploying.
Launch 3 research agents in parallel — market, users, tech — fast answers
Guides creation of best-practice agent skills following the open format specification. Covers frontmatter, directory structure, progressive disclosure, reference files, rules folders, and validation. Use when creating a new skill, authoring SKILL.md, setting up a rules-based audit skill, structuring a skill bundle, or asking "how to write a skill."
[PREREQUISITE] Install and configure Godot MCP server for programmatic scene manipulation via Model Context Protocol. Use when user explicitly requests MCP-based scene building or automation. NOT for manual Godot workflows. Keywords MCP, Model Context Protocol, scene automation, npx, claude_desktop_config.
Parameter-efficient fine-tuning with Low-Rank Adaptation (LoRA). Use when fine-tuning large language models with limited GPU memory, creating task-specific adapters, or when you need to train multiple specialized models from a single base.
Build AI-first applications with RAG pipelines, embeddings, vector databases, agentic workflows, and LLM integration. Master prompt engineering, function calling, streaming responses, and cost optimization for 2025+ AI development.
Use when setting up, deploying, or operating vLLM Studio (env keys, controller/frontend startup, Docker services, branch workflow, and release checklists).
Expert-level precision agriculture, farm management systems, crop monitoring, and agtech