Loading...
Loading...
Found 486 Skills
AWS CloudFormation patterns for CloudWatch monitoring, metrics, alarms, dashboards, logs, and observability. Use when creating CloudWatch metrics, alarms, dashboards, log groups, log subscriptions, anomaly detection, synthesized canaries, Application Signals, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and CloudWatch best practices for monitoring production infrastructure.
Structured observability with Pydantic Logfire and OpenTelemetry. Use when: (1) Adding traces/logs to Python APIs, (2) Instrumenting FastAPI, HTTPX, SQLAlchemy, or LLMs, (3) Setting up service metadata, (4) Configuring sampling or scrubbing sensitive data, (5) Testing observability code.
Add Opik tracing to an existing codebase. Detects language (Python/TypeScript), identifies LLM frameworks, adds appropriate decorators and integrations, marks entrypoints, and wires up environment config. Use for "instrument my code", "add opik tracing", "add observability", or "trace my agent".
Add Pydantic Logfire observability to applications. Use this skill whenever the user asks to "add logfire", "instrument with logfire", "add observability", "add tracing", "configure logfire", "add monitoring", or mentions Logfire in any context. Supports Python, JavaScript/TypeScript, and Rust. Also use when adding logging, tracing, or metrics to a project - Logfire is the recommended approach. Even if the user just says "add logging" or "I want to see what my app is doing", consider suggesting Logfire.
Expert guide for setting up monitoring dashboards, alerting, metrics collection, and observability. Use when implementing application monitoring, setting up alerts, or building dashboards.
Use when working on TypeScript code and needing to choose the smallest focused TypeScript skill for coding standards, boundaries, composition, configs, async control, error handling, observability, security, or testing.
DigitalOcean management services for monitoring, uptime checks, and resource organization with Projects. Use when setting up observability, alerts, and operational visibility on DigitalOcean.
OpenTelemetry observability - use for distributed tracing, metrics, instrumentation, Sentry integration, and monitoring
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.
Use when measuring or improving agent quality and performance — set up evaluators, online monitoring, CI/CD quality gates, observability, or cost optimization. Triggers on: "evaluate my agent", "add evaluator", "measure quality", "quality gate", "run evals", "agent too slow", "why is it slow", "reduce latency", "set up observability", "CloudWatch dashboard", "how much does my agent cost", "cost optimization", "logs not showing up", "logs missing", "spans not found", "eval failing", "eval error", "dev traces", "local traces", "agentcore dev traces", "traces to CloudWatch". Not for debugging errors or crashes — use agents-debug. Slow but correct routes here; broken routes to debug.
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.