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Found 493 Skills
Postgres-backed observability and policy store for the skill system. Provides tables for policy profiles (effect allowlists), skill execution runs, and step-level events. Use when setting up the skill system database or querying execution history.
Axiom observability API for logs and analytics. Use when user mentions "logs", "query logs", "Axiom", or asks about event analytics.
This skill should be used when the user asks to "investigate an issue", "debug a problem", "find out why something is slow", "check error rates", "analyze user behavior", "understand a production incident", "query telemetry data", "look at logs", "check traces", "examine spans", "analyze RUM data", "check frontend performance", "investigate backend latency", "find transaction data", "check payment metrics", "analyze user journeys", or wants to answer questions using observability data from logs, metrics, traces, RUM, or APM - this is the gateway skill for deciding where to look first.
Explain what an existing SigNoz dashboard shows in plain operational language — the panels, queries, variables, and what to watch for on each. Make sure to use this skill whenever the user asks "explain this dashboard", "what does my [X] dashboard show", "walk me through the panels", "what should I watch for on this dashboard", or "help me understand this dashboard", or otherwise asks for an interpretation of a dashboard's contents — even if they don't say "explain" explicitly. Also use it when someone is onboarding to a service and wants to understand what its existing observability looks like.
Guides microservice design and delivery—bounded contexts, service boundaries, REST/gRPC/event APIs, sync vs async tradeoffs, resilience (timeouts, retries, circuit breakers, bulkheads), per-service data ownership, saga and outbox patterns, twelve-factor containers, observability (logs, metrics, trace propagation), API versioning at gateways/meshes, and contract testing. Use for microservices developer, service boundary, bounded context, gRPC between services, circuit breaker, saga pattern, outbox pattern, twelve-factor, contract testing microservices, service decomposition, or event-driven microservice—not K8s platform ops (platform-engineer, site-reliability-engineer), enterprise iPaaS (enterprise-integration-api-developer), monolith-first apps (senior-software-engineer), or classified pipelines (classified-software-devsecops-engineer).
Take your AI agent to the next level with full LangWatch integration. Adds tracing, prompt versioning, evaluation experiments, and simulation tests in one go. Use when the user wants comprehensive observability, testing, and prompt management for their agent.
Query Langfuse traces for debugging LLM calls, analyzing token usage, and investigating workflow executions. Use when debugging AI/LLM behavior, checking trace data, or analyzing observability metrics.
Orchestrate multi-service AWS workflows with autonomous agents. Coordinates across compute, storage, identity, and observability services for intelligent cloud automation.
Build production-ready gRPC services in Go with mTLS, streaming, and observability. Use when designing Protobuf contracts with Buf or implementing secure service-to-service transport.
ABSOLUTE MUST to debug and inspect LLM/AI agent traces using PostHog's MCP tools. Use when the user pastes a trace URL (e.g. /llm-observability/traces/<id>), asks to debug a trace, figure out what went wrong, check if an agent used a tool correctly, verify context/files were surfaced, inspect subagent behavior, investigate LLM decisions, or analyze token usage and costs.
Build search applications and query log analytics data with OpenSearch. Use this skill when the user mentions OpenSearch, search app, index setup, search architecture, semantic search, vector search, hybrid search, BM25, dense vector, sparse vector, agentic search, RAG, embeddings, KNN, PDF ingestion, document processing, or any related search topic. Also use for log analytics and observability — when the user wants to set up log ingestion, query logs with PPL, analyze error patterns, set up index lifecycle policies, investigate traces, or check stack health. Activate even if the user says log analysis, Fluent Bit, Fluentd, Logstash, syslog, traceId, OpenTelemetry, or log analytics without mentioning OpenSearch.
FastAPI OpenTelemetry style: native FastAPIInstrumentor, centralized observability init, Python decorators, OTLP logs, and LLM cost metrics.