Loading...
Loading...
Found 1,140 Skills
Use when "Polars", "fast dataframe", "lazy evaluation", "Arrow backend", or asking about "pandas alternative", "parallel dataframe", "large CSV processing", "ETL pipeline", "expression API"
Complex research requiring deeper analysis, multi-step reasoning, and sophisticated source evaluation for technical, academic, or specialized domain queries needing expert-level analysis, high-stakes decisions, or multi-layered problem solving.
Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles
Evaluate research rigor. Assess methodology, experimental design, statistical validity, biases, confounding, evidence quality (GRADE, Cochrane ROB), for critical analysis of scientific claims.
Comprehensive quality auditing and evaluation of tools, frameworks, and systems against industry best practices with detailed scoring across 12 critical dimensions
Implement feature flags using the Vercel Flags SDK with server-side evaluation, environment-based toggles, and Vercel Toolbar integration.
Systematically evaluate completed short stories or novel chapters to identify strengths, weaknesses, and improvement opportunities. Use after drafting to assess whether the piece achieves its narrative goals.
Validate existing offers using Hormozi's Value Equation. Scores offers, exposes weaknesses, and provides actionable fixes. Activates for "validate my offer," "rate my offer," or "is my offer good."
Audit npm, pip, and Go dependencies that OpenClaw skills try to install. Checks for known vulnerabilities, typosquatting, and malicious packages.
Expert in designing effective prompts for LLM-powered applications. Masters prompt structure, context management, output formatting, and prompt evaluation. Use when "prompt engineering, system prompt, few-shot, chain of thought, prompt design, LLM prompt, instruction tuning, prompt template, output format, prompts, llm, gpt, claude, system-prompt, few-shot, chain-of-thought, evaluation" mentioned.
Designs retrieval-augmented generation pipelines for document-based AI assistants. Includes chunking strategies, metadata schemas, retrieval algorithms, reranking, and evaluation plans. Use when building "RAG systems", "document search", "semantic search", or "knowledge bases".
Review and improve documentation with parallel evaluation and iterative improvement loop.