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Found 1,406 Skills
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.
Check GitHub Actions workflow status after git push using gh CLI. Reports CI status, identifies failing jobs, and suggests local reproduction commands. Use after "git push", when user asks about CI status, workflow failures, or build results. Use for "check CI", "workflow status", "actions failing", or "build broken". Do NOT use for local linting (use code-linting), debugging test failures locally (use systematic-debugging), or setting up new workflows.
Intelligent interaction performance analysis with automated workflows for INP debugging, scroll jank investigation, and main thread blocking. Includes decision trees that automatically run script attribution when long frames detected, break down input latency phases, and correlate layout shifts with interactions. Features workflows for complete interaction audit, third-party script impact analysis, and animation performance debugging. Cross-skill integration with Core Web Vitals (INP/CLS correlation) and Loading (script execution analysis). Use when the user asks about slow interactions, janky scrolling, unresponsive pages, or INP optimization. Compatible with Chrome DevTools MCP.
Use whenever creating, modifying, or debugging payment modules in QloApps — offline methods and online payment gateways. Covers PaymentModule class, payment hooks, checkout integration, validateOrder flow, API credentials, webhook handling, transaction logging, and refunds.
JavaScript reverse engineering and browser debugging MCP server with anti-detection and agent-first tooling
Manages Google Cloud Pub/Sub topics, subscriptions, schemas, and messages safely and efficiently. Use when building or managing event-driven, decoupled systems, streaming data pipelines, or integrating push/pull asynchronous message consumers. Don't use when writing or debugging Google Cloud client library code or raw REST/gRPC API interactions directly.
Master systematic debugging techniques, profiling tools, and root cause analysis to efficiently track down bugs across any codebase or technology stack. Use when investigating bugs, performance issues, or unexpected behavior.
Code quality orchestrator enforcing TRUST 5 validation, proactive code analysis, linting standards, and automated best practices. Use when performing code review, quality gate checks, lint configuration, TRUST 5 compliance validation, or establishing coding standards. Do NOT use for writing tests (use moai-workflow-testing instead) or debugging runtime errors (use expert-debug agent instead).
Use when debugging 'file not syncing', 'CloudKit error', 'sync conflict', 'iCloud upload failed', 'ubiquitous item error', 'data not appearing on other devices', 'CKError', 'quota exceeded' - systematic iCloud sync diagnostics for both CloudKit and iCloud Drive
Cloudflare Workers observability with logging, Analytics Engine, Tail Workers, metrics, and alerting. Use for monitoring, debugging, tracing, or encountering log parsing, metric aggregation, alert configuration errors.
Comprehensive DAG failure diagnosis and root cause analysis. Use for complex debugging requests requiring deep investigation like "diagnose and fix the pipeline" or "full root cause analysis".
Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.