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Found 2,058 Skills
Run isolated eval and grading calls using CC 2.1.81 --bare mode. Constructs claude -p --bare invocations for skill evaluation, trigger testing, and LLM grading without plugin/hook interference. Use when running eval pipelines, grading skill outputs, benchmarking prompt quality, or testing trigger accuracy in isolation.
Execute a comprehensive React Project Health Audit. Analyzes tech stack, architecture, state management, testing, code quality, performance, CI/CD, and documentation. Produces a Google Docs-ready report with section scores and weighted overall score. Use when the user asks to audit a React project, run a health check, evaluate frontend quality, or assess technical debt. Triggers on: 'react audit', 'health audit', 'react health', 'frontend audit', 'next.js audit', 'vite audit', 'project quality check'.
Code-first Netra best-practices playbook covering setup, instrumentation, context tracking, custom spans/metrics, integration patterns, evaluation, simulation, and troubleshooting.
Critical analysis of research papers, academic manuscripts, preprints, and technical studies — evaluating methodology, claims-evidence alignment, contribution significance, and intellectual honesty. Produces coherent analytical responses (not checklists) that distinguish genuine weaknesses from standard field limitations. Governs intellectual posture: collegial reader, not adversarial reviewer. Triggers on: "critique this paper", "review this research", "what do you think of this paper", "analyze this study", "evaluate the methodology", "is this paper sound", "assess this research", "strengths and weaknesses of this paper", "does the evidence support the claims". Use this skill when the user provides a research paper, preprint, or technical study and asks for critical evaluation of its scientific merit, methodology, or contribution — not formatting, citation hygiene, or submission readiness (use manuscript-review for those).
Activates Warren Buffett's complete investment thinking system. The following scenarios must trigger it: analyzing any stock or company, evaluating investment opportunities, interpreting financial reports/annual reports/shareholder letters, assessing business moats or competitive advantages, evaluating management quality and integrity, making buy/hold/sell decisions, understanding core value investing concepts (compounding/intrinsic value/margin of safety/circle of competence/Mr. Market), analyzing any industry (insurance/banking/consumer/media/energy/railroads/technology), handling capital allocation/buybacks/dividends questions, assessing market sentiment and macro risks, exploring when to sell, analyzing institutional imperative or management behavior. Even if the user does not mention "Buffett," proactively trigger whenever the topic involves investment analysis, business quality assessment, or investment decision-making.
Apply Difference-in-Differences (DID) to estimate causal treatment effects by comparing changes in outcomes between treatment and control groups. Use this skill when the user evaluates policy interventions, natural experiments, or regulatory changes, needs to test parallel trends, or when they ask 'did this policy work', 'how do I identify causal effects without randomization', or 'what is the treatment effect'.
Find and evaluate research datasets for any scientific question. Teaches how to reason about data needs, search across public repositories, evaluate dataset fitness, and identify access requirements. Use whenever users ask to find data, search for datasets, identify cohort studies, or need data for analysis. Also use when users ask about a specific survey or cohort (NHANES, HRS, UK Biobank, TCGA, etc.), when they want to know what data exists for a research question, or when they need to compare available data sources. If the user mentions "where can I get data" or "is there a dataset for X", this is the right skill.
Migrate an application with hardcoded LLM prompts to a full LaunchDarkly AgentControl implementation in five stages: audit the code, wrap the call, move the tools, add tracking, attach evaluators. Use when the user wants to externalize model/prompt configuration, move from direct provider calls (OpenAI, Anthropic, Bedrock, Gemini, Strands) to a managed config, or stage a full hardcoded-to-LaunchDarkly migration.
Help users conduct effective hiring interviews. Use when someone is designing an interview loop, crafting interview questions, evaluating candidates in real-time, or building a structured interview process.
Complete RAG and search engineering skill. Covers chunking strategies, hybrid retrieval (BM25 + vector), cross-encoder reranking, query rewriting, ranking pipelines, nDCG/MRR evaluation, and production search systems. Modern patterns for retrieval-augmented generation and semantic search.
AWS cost optimization and FinOps workflows. Use for finding unused resources, analyzing Reserved Instance opportunities, detecting cost anomalies, rightsizing instances, evaluating Spot instances, migrating to newer generation instances, implementing FinOps best practices, optimizing storage/network/database costs, and managing cloud financial operations. Includes automated analysis scripts and comprehensive reference documentation.
Score content against GEO optimization criteria. Triggers on "score this", "rate content", "GEO score", "how does this rank", "evaluate content", "content score".