agent-observability-eval-bootstrap
bydatadog-labs· 37 skills
Bootstrap evaluators from production traces — by default propose online LLM-judge evaluators and, after you confirm, create them in Datadog as disabled drafts (never auto-enabled); on request emit Python SDK code or a framework-agnostic JSON spec instead. Use when user says "bootstrap evaluators", "generate evaluators", "create evals from traces", "eval bootstrap", "write evaluators", "build eval suite", "publish evaluators", or wants to generate BaseEvaluator/LLMJudge code or online judge configs from production LLM trace data. Works with ml_app and optional RCA report or failure hypothesis.
How to install agent-observability-eval-bootstrap?
datadog-labs/agent-skills/agent-observability-eval-bootstrap
$npx -y skills add datadog-labs/agent-skills --skill agent-observability-eval-bootstrapInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/datadog-labs/agent-skills" --skill "datadog-labs/agent-skills/agent-observability-eval-bootstrap"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/datadog-labs/agent-skills" that are relevant to the current task. Run `npx skills add "https://github.com/datadog-labs/agent-skills"` and select the relevant skills, then follow their instructions.
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