Loading...
Loading...
Found 1,140 Skills
Evaluate Agent Skill design quality against official specifications and best practices. Use when reviewing, auditing, or improving SKILL.md files and skill packages. Provides multi-dimensional scoring and actionable improvement suggestions.
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.
Structured manuscript/grant review with checklist-based evaluation. Use when writing formal peer reviews with specific criteria methodology assessment, statistical validity, reporting standards compliance (CONSORT/STROBE), and constructive feedback. Best for actual review writing, manuscript revision. For evaluating claims/evidence quality use scientific-critical-thinking; for quantitative scoring frameworks use scholar-evaluation.
Build production Spring Boot applications - REST APIs, Security, Data, Actuator
Create or evaluate an architecture decision record (ADR). Use when choosing between technologies (e.g., Kafka vs SQS), documenting a design decision with trade-offs and consequences, reviewing a system design proposal, or designing a new component from requirements and constraints.
Instrument Python LLM apps, build golden datasets, write eval-based tests, run them, and root-cause failures — covering the full eval-driven development cycle. Make sure to use this skill whenever a user is developing, testing, QA-ing, evaluating, or benchmarking a Python project that calls an LLM, even if they don't say "evals" explicitly. Use for making sure an AI app works correctly, catching regressions after prompt changes, debugging why an agent started behaving differently, or validating output quality before shipping.
Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.
Use this skill when gathering knowledge at scale before making decisions - technology evaluation, SOTA analysis, codebase archaeology, competitive analysis, or any investigation requiring multiple sources. Activates on mentions of research, investigate, evaluate options, what's the best, compare alternatives, state of the art, deep dive, explore the landscape, or find out how.
Benchmark any agent skill to measure whether it actually improves performance. Use when the user wants to evaluate, test, or compare a skill against baseline, or when they mention "benchmark", "eval", "skill performance", or "does this skill help". Runs isolated eval sessions with and without the skill, grades outputs via layered grading (deterministic checks + LLM-as-judge), analyzes behavioral signals, and generates a comparison report with a USE / DON'T USE verdict.
A systematic stock analysis framework based on Warren Buffett's value investing philosophy. It provides a complete investment analysis process including economic moat analysis, financial evaluation, management assessment, valuation methods and risk control. Suitable for evaluating specific stocks, screening high-quality targets, analyzing competitive advantages, and building investment portfolios. Activate when users mention keywords such as "Buffett", "value investing", "economic moat", "ROE", "pricing power", "long-term holding", "margin of safety", "circle of competence", "white horse stock", "blue chip stock", or when stock investment analysis is required.
Investment Analysis: Generate an in-depth investment analysis report. We do not conduct traditional investment analysis—the core judgment is whether the project is an "Order-Creating Machine". Activate this when the user says "investment report", "investment analysis", "analyze this project", "write an investment report", "investment report", "invest analysis", or provides entrepreneur conversation records for investment evaluation. Also activate when the user pastes or references meeting notes, pitch decks, or founder interviews and requests analysis.