skills

The way to make an AI agent report what it did to AgentEye — planning what to record, writing the instrumentation, and proving the events land. Reach for it on vague phrasing too: "add observability to my agent", "why isn't my agent showing up?" Trigger when the user wants to: • plan an integration — which points in their agent loop to record, and what the platform must see before sessions, errors, and evals work at all; • write or fix instrumentation — add the `agenteye` Python SDK to an agent codebase, thread session/agent identity through it, emit tool, model, hook, or human events; • verify it — confirm events are being written, or debug an integration that looks correct and produces nothing. Served by the `agenteye` Python SDK, inside the user's own agent. NOT for reading telemetry that already landed or operating a deployment (that's `agenteye-cli`), or building the evaluator service that scores runs (that's `agenteye-evaluator`).

The way to put automatic quality scores on an AI agent's production runs — both deciding what is worth measuring and building the service that measures it. Reach for it even on vague phrasing like "I want evals" or "how do I know if my agent is any good?" Trigger when the user wants to: • decide what to score — they know their agent is sometimes bad but not which dimensions to track, or want scores grounded in what their real sessions show; • build or change an evaluator — scaffold the scoring service, add a dimension, score with rules or an LLM judge, test it against a real captured session, deploy it and confirm scores land. Served by the `agenteye-evaluator` Python SDK, with the `agenteye` CLI supplying real session data to design against. NOT for reading eval results that already exist or checking whether quality dropped (that's `agenteye-cli` — `agenteye evals`), instrumenting an agent with the AgentEye SDK, or alerting on scores.

The way to answer "how are my production AI agents doing?" and to run the team's agent-observability deployment — reach for it even on casual phrasing that names no tool. Trigger when the user wants to: • inspect agent telemetry — did agents error/fail/go flaky; sessions, events, latency, token usage, slowest models; eval/quality scores and whether quality dropped; • operate the deployment — ack/assign/resolve firing alerts and incidents with notes; see who has access and change roles (e.g. make someone read-only); create or scope API keys (e.g. a CI key that only pushes events); change settings; run saved or ad-hoc ClickHouse queries. Served by the `agenteye` CLI against an AgentEye platform. NOT for adding SDK/instrumentation to your app, debugging the collector/daemon, or unrelated dev work (why a build/CI run failed, rotating non-AgentEye secrets).