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Found 307 Skills
Help a CS or AI PhD student design hypothesis-driven experiments with baselines, variables, metrics, controls, logging, and stop conditions. Use this skill whenever the user is about to run experiments, compare models, plan an ablation, debug inconclusive results, prepare an experiment section, or wants to avoid changing too many things at once.
This skill should be used when adding error tracking and performance monitoring with Sentry and OpenTelemetry tracing to Next.js applications. Apply when setting up error monitoring, configuring tracing for Server Actions and routes, implementing logging wrappers, adding performance instrumentation, or establishing observability for debugging production issues.
Structured JSON logging with correlation IDs, request context propagation across async boundaries, performance timing decorators, and worker metrics collection.
Generate Chi HTTP handlers following GO modular architechture conventions (request/response DTOs, use case orchestration, error handling, swagger annotations, Fx DI). Use when creating HTTP endpoint handlers in internal/modules/<module>/http/chi/handler/ for REST operations (List, Create, Update, Delete, Get) that need to decode requests, call use cases, map responses, and handle errors with proper logging and tracing.
Use when adding logging to services, setting up monitoring, creating alerts, debugging production issues, designing SLIs/SLOs, or implementing structured logging (Pino, Winston), metrics (Prometheus, DataDog, CloudWatch), or distributed tracing (OpenTelemetry).
Database operations: migrations, queries, transactions, and performance. Use when: - Writing database migrations - Optimizing queries or adding indexes - Managing transactions and connections - Setting up connection pooling - Designing audit logging Keywords: database, migration, SQL, query optimization, index, transaction, connection pool, N+1, ORM, audit log
Observability patterns for metrics, logging, distributed tracing, and error tracking. Trigger: When setting up monitoring, when implementing logging, when adding error tracking, when configuring distributed tracing, when building health checks, when creating dashboards.
Technical safeguards and architectural patterns for building HIPAA-compliant software on AWS. Use when building healthcare SaaS, handling PHI (Protected Health Information), designing patient data systems, implementing healthcare APIs, setting up HIPAA-eligible AWS infrastructure, reviewing code for PHI exposure, designing audit logging, or when the user mentions patients, medical records, EHR/EMR, health data, HL7, FHIR, or covered entities. Essential for founders and developers building in healthcare or digital health space.
Guidelines for structured logging, distributed tracing, and debugging patterns across languages. Covers logging best practices, observability, security considerations, and performance analysis.
This skill should be used when the user asks to "harden code", "security hardening", "improve security posture", "add security headers", "tighten security", "defensive coding suggestions", or "proactive security improvements". Also triggers when the user asks about CSP, CORS hardening, rate limiting, input validation improvements, security logging, or defense-in-depth measures.
Specialized skill for implementing proper error handling, logging, user-friendly error messages, and error recovery strategies. Use when implementing error handling in APIs, components, or when debugging error issues.
GDPR compliance implementation. Data subject rights (access, deletion, portability), consent management, data processing records, PII handling, and privacy by design patterns. USE WHEN: user mentions "GDPR", "data privacy", "right to be forgotten", "data deletion", "consent management", "PII", "data subject request", "privacy policy", "cookie consent" DO NOT USE FOR: authentication - use auth skills; encryption - use `cryptography`; audit logging - use `audit-logging`