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Found 850 Skills
Filesystem RAG benchmarks: corpus/, train.json, evaluate_rag.py (RAGAS quality). Not for prod monitoring, latency/throughput benchmarking (use rag-perf), or evals outside this repo layout.
Brain-augmented web research. Sends brain context about a topic to Perplexity, which searches the web with citations and returns what is NEW vs what the brain already knows. Use for entity enrichment, current-state checks, deal monitoring, and freshness deltas. NOT for simple URL fetches (use web_fetch) or brain-only queries (use gbrain query).
Router and overview for the Cargo CLI agent skills. Explains the eleven skills (one outcome skill cargo-gtm + ten capability skills), the UUID flow between them, async polling, end-to-end use cases (enrich one record, enrich and sync to CRM, AI lead scoring, custom workflow, error monitoring, fresh-workspace bootstrap, segment export, GTM context authoring), and common gotchas (`conjonction` spelling, run vs batch, model-uuid vs segment-uuid). Load first whenever working with the Cargo CLI, when unsure which sub-skill applies, when stitching multiple sub-skills together, when bootstrapping a workspace, or when the user asks about Cargo skills in general.
Collect search results from Kuaishou — matching posts, URLs, authors, engagement. Use when the user wants to collect content matching keywords for research or monitoring.
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.
Implement distributed tracing with correlation IDs, trace propagation, and span tracking across microservices. Use when debugging distributed systems, monitoring request flows, or implementing observability.
Expert in setting up Sentry error tracking and Google Analytics for NestJS and Next.js applications. Use this skill when users need monitoring, error tracking, or analytics configuration.
Reporting framework for monitoring trust, sentiment, and regulator-facing KPIs.
Manage concurrent background workers with scheduling, dependencies, health monitoring, and automatic disabling of failing workers.
Zero Script QA - Testing methodology without test scripts. Uses structured JSON logging and real-time Docker monitoring for verification. Use proactively when user needs to verify features through log analysis instead of test scripts. Triggers: zero script qa, log-based testing, docker logs, 제로 스크립트 QA, ゼロスクリプトQA, 零脚本QA, QA sin scripts, pruebas basadas en logs, registros de docker, QA sans script, tests basés sur les logs, journaux docker, skriptloses QA, log-basiertes Testen, Docker-Logs, QA senza script, test basati sui log, log docker Do NOT use for: unit testing, static analysis, or projects without Docker setup.
Provides comprehensive patterns for deploying Next.js applications to production. Use when configuring Docker containers, setting up GitHub Actions CI/CD pipelines, managing environment variables, implementing preview deployments, or setting up monitoring and logging for Next.js applications. Covers standalone output, multi-stage Docker builds, health checks, OpenTelemetry instrumentation, and production best practices.
Twitter/X integration with three modes: official API v2 search/research via x-search (pay-per-use, $0.005/read), session-based posting/reading via bird CLI (free, browser cookies), and bookmark archival via Smaug. This skill should be used when searching tweets, researching topics on X, posting, monitoring accounts, or archiving bookmarks.