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Found 3,048 Skills
Runs this project's full validation suite — tests, type checks, and linting across every part of the stack — then reports overall health. Use before committing, before opening a PR, or after finishing a chunk of work to confirm zero regressions.
Design LLM-as-Judge evaluators for subjective criteria that code-based checks cannot handle. Use when a failure mode requires interpretation (tone, faithfulness, relevance, completeness). Do NOT use when the failure mode can be checked with code (regex, schema validation, execution tests). Do NOT use when you need to validate or calibrate the judge — use validate-evaluator instead.
When you want to pressure-test a potential new business, product, or side project against the serial-founder filter. Not "marketing ideas for a product" (that's marketing-skills:marketing-ideas) — this is "should this business exist + can you win it." Runs the idea through a structured framework (problem, audience, wedge, monetization, moat, portfolio fit, distribution, energy fit, opportunity cost), checks domain availability via /domain, optionally triggers /deep-research for market validation, and outputs a viability brief: build / sleep on it / pass. Archives every idea to ~/.config/makerskills/business-brainstorm/archive/ so past work is searchable. Triggers on "/business-brainstorm," "/brainstorm," "new business idea," "should I build X," "pressure test this idea," "validate this idea," "is X a good business," "what about a [type] for [audience]."
Debug FastAPI applications systematically with this comprehensive troubleshooting skill. Covers async/await issues, Pydantic validation errors (422 responses), dependency injection failures, CORS configuration problems, database session management, and circular import resolution. Provides structured four-phase debugging methodology with FastAPI-specific tools including uvicorn logging, OpenAPI docs, and middleware debugging patterns.
Move validation and authorization into Form Requests; use rule objects, custom messages, and nested data handling to keep controllers slim
Pre-deployment validation for Webflow Code Components. Checks bundle size, dependencies, prop configurations, SSR compatibility, styling setup, and common issues before running webflow library share.
Error handling strategy for .NET 10 applications. Covers the Result pattern, ProblemDetails (RFC 9457), global exception handling, FluentValidation, and structured error responses. Load this skill when implementing error handling, validation, or designing API error contracts, or when the user mentions "error handling", "Result pattern", "ProblemDetails", "exception", "validation", "FluentValidation", "error response", "global exception handler", or "RFC 9457".
Caching strategies for .NET 10 applications. Covers HybridCache (the default), output caching, response caching, and distributed cache patterns. Load this skill when implementing caching, optimizing read performance, reducing database load, or when the user mentions "cache", "HybridCache", "Redis", "output cache", "response cache", "distributed cache", "IMemoryCache", "cache invalidation", "stampede protection", or "cache-aside".
Provides guidance for authoring Apache Airflow DAGs in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Covers environment context discovery, Airflow 2 vs 3 compatibility, authoring best practices, and local/remote validation processes. Use when creating or extending an Airflow DAG. Don't use when authoring Python code unrelated to Airflow DAGs.
Debug Scikit-learn issues systematically. Use when encountering model errors like NotFittedError, shape mismatches between train and test data, NaN/infinity value errors, pipeline configuration issues, convergence warnings from optimizers, cross-validation failures due to class imbalance, data leakage causing suspiciously high scores, or preprocessing errors with ColumnTransformer and feature alignment.
Use framework caches and value/query caching to reduce work; add tags, locks, and explicit invalidation strategies for correctness
Multi-layer validation pattern - validates data at EVERY layer it passes through to make bugs structurally impossible, not just caught.