AI tools for “observability”
83 results (tools & skills) · 205 ms · understood as by meaning
…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…
Analyze the most expensive users in AI observability and explain why they cost so much. Use when the user asks about top spenders, expensive users, per-user LLM cost, user-level cost drivers, or patterns behind high AI…
…traces, logs, and metrics to DataRobot for monitoring, observability, and governance. Use when the user says "add tracing/observability/monitoring to my agent", wants to instrument an existing agent project in…
…to forward LLM and API spend to your own observability system. Use when adding cost/spend logging, building a cost observability integration, or forwarding per-request cost data to an external…
…DCU/cost consumption, idle/zombie clusters, or workload observability (use @skill:gcp-spark-observability). - Troubleshooting failed Spark jobs or Dataproc batches (use…
Add Pydantic Logfire observability to application code — traces, logs, metrics, and AI/agent spans. Use when the user asks to add or configure Logfire, observability, tracing, logging, or monitoring; maximize useful…
…Use when the user pastes a trace or session URL (e.g. /ai-observability/traces/<id> or /ai-observability/sessions/<id>), asks to debug a trace, figure out what went wrong, check if an agent used a tool correctly,…
…AI gateway, LLM calls, realtime, logs, Loki, Grafana, observability, postgres, database, backend, Claimable Neon, neon.new, a no-signup database, or pairing Neon with Upstash for cache, Redis, rate limiting,…
Investigate AI observability clusters — understand usage patterns in AI/LLM traffic, compare cluster behavior, compute cost/latency metrics, and drill into individual traces within clusters.
A concise feature matrix for deciding which PlanetScale safety, observability, and automation recommendations apply by engine.
…products), payments (checkout, subscriptions, billing), observability/monitoring, messaging/email, search, or CMS — or when discovering, installing, or managing…
…`authoring-scouts` for edits, `exploring-scouts` for run observability, and `inbox-exploration` for report triage. Trigger on "work with my scouts", "get more out of scouts", "have a scout watch X", "tell me if Y…
…guardrails, query rewriting, models, search, ingestion, observability, summarization, reasoning, and…
…instrumentation, infrastructure, evals, frontend observability, Gateway, or coding agents. Use for "set up Logfire", "add Logfire to my project", "get me set up properly with Logfire", "send as much data as…
…or SDK usage, or (3) do any AI engineering task (AI observability, prompt engineering/management, evaluation and evaluator management, experimentation, dataset management, evaluation-driven CI/CD, feedback…
Guides Qdrant monitoring and observability setup. Use when someone asks 'how to monitor Qdrant', 'what metrics to track', 'is Qdrant healthy', 'optimizer stuck', 'why is memory growing', 'requests are slow', 'set up…
Diagnoses Qdrant production issues using metrics and observability tools. Use when someone reports 'optimizer stuck', 'indexing too slow', 'memory too high', 'OOM crash', 'queries are slow', 'latency spike', or 'search…
MLflow tracing and observability on Databricks. Use when getting started with MLflow, instrumenting GenAI apps and agents, retrieving and analyzing traces, debugging chat sessions, or querying aggregate trace metrics on…
…including natural-language Grafana Assistant questions and observability investigations. Covers setup, OAuth authorization, read/write access scopes, choosing tools, and best practices for context window management.…
…a new project from scratch — questions about Datadog observability products (logs, metrics, APM, traces, monitors, dashboards), working inside an existing project, deploying, publishing, auth, or…