Loading...
Loading...
Found 1,482 Skills
Use when working with Payload CMS projects (payload.config.ts, collections, fields, hooks, access control, Payload API). Triggers on tasks involving: collection definitions, field configurations, hooks, access control, database queries, custom endpoints, authentication, file uploads, drafts/versions, live preview, or plugin development. Also use when debugging validation errors, security issues, relationship queries, transactions, or hook behavior.
Guide for implementing license key management with Dodo Payments - activation, validation, and access control for software products.
Automated code review workflow using OpenAI Codex CLI. Implements iterative fix-and-review cycles until code passes validation or reaches iteration limit. Use when building features requiring automated code validation, security checks, or quality assurance through Codex CLI.
Zod schema validation patterns for TypeScript applications. Use when validating API responses, form data, environment variables, or any runtime data. Type-safe validation with automatic TypeScript inference.
Data validation patterns including schema validation, input sanitization, output encoding, and type coercion. Use when implementing validate, validation, schema, form validation, API validation, JSON Schema, Zod, Pydantic, Joi, Yup, sanitize, sanitization, XSS prevention, injection prevention, escape, encode, whitelist, constraint checking, invariant validation, data pipeline validation, ML feature validation, or custom validators.
Expert guidance for ElysiaJS web framework development. Use when building REST APIs, GraphQL services, or WebSocket applications with Elysia on Bun. Covers routing, lifecycle hooks, TypeBox validation, Eden type-safe clients, authentication with JWT/Bearer, all official plugins (OpenAPI, CORS, JWT, static, cron, GraphQL, tRPC), testing patterns, and production deployment. Assumes bun-expert skill is active for Bun runtime expertise.
Use when building or reviewing service, job, or CLI runtime behavior in Python — designing startup validation, shutdown sequences, observability, and structured logging. Also use when startup crashes from late config, shutdown leaves orphaned processes, terminal states are implicit, or logs lack structure.
Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.
Complete HUMMBL Base120 mental models framework with all 120 models across 6 transformations (Perspective, Inversion, Composition, Decomposition, Recursion, Meta-Systems). Includes model selection guidance, application methodology, and validation checklist. Version 1.0-beta definitive reference.
Operational patterns, templates, and decision rules for time series forecasting (modern best practices): tree-based methods (LightGBM), deep learning (Transformers, RNNs), future-guided learning, temporal validation, feature engineering, generative TS (Chronos), and production deployment. Emphasizes explainability, long-term dependency handling, and adaptive forecasting.
POC validation patterns to catch issues before committing to long-running ML experiments. TRIGGERS - fail-fast, POC validation, preflight check, experiment validation, schema validation, gradient check, sanity check, smoke test.
Skill for writing fluent and readable test assertions with AwesomeAssertions. Use it when you need to write clear assertions, compare objects, validate collections, or handle complex comparisons. Covers complete APIs such as Should(), BeEquivalentTo(), Contain(), ThrowAsync(), etc. Keywords: assertions, awesome assertions, fluent assertions, Should(), Be(), BeEquivalentTo, Contain, ThrowAsync, NotBeNull, object comparison, collection validation, exception assertion, AwesomeAssertions, FluentAssertions, fluent syntax