
Claude agent with tools and evals
Quest Build a Claude Agent SDK app with its own MCP server, then trace and evaluate it
- Hero
- Claude Code
- Weapon
Claude Opus 5.5- Charge
Anthropic Agent SDK Dev
Anthropic MCP Builder
MLflow Skills
MLflow skills to add tracing to an AI app, debug failing traces, build scorers and run agent evaluations.
Foe: Mirage Djinn, an AI answer that sounds right but isn't.
Foes
Party · Context
The Mirage Djinn blocks the way.
What really happensIt stands for an AI answer that sounds right but isn't.
Summoner: Context 100/100.
The djinn conjures a mirage, and the hero swings at nothing.
What really happensA model can sound sure and still be wrong, so AI features need evals and checks.
Summoner takes 8. Summoner: Context 92/100.
The MLflow kit opens its tracing scrolls.
What really happensinstrumenting-with-mlflow-tracing adds MLflow Tracing to your Python or TypeScript app and its LLM library.
Mirage Djinn takes 28.
Footprints show where the agent took a wrong turn.
What really happensanalyze-mlflow-trace and debug-agent read spans and assessments and connect them to your code.
Mirage Djinn takes 23.
The Mirage Djinn uses Mirage.
Summoner takes 8. Summoner: Context 84/100.
The hero sets up judges for the next trial.
What really happensbuild-a-scorer turns your quality rules into code checks, built-in scorers or LLM judges.
Mirage Djinn takes 35.
The agent is tested before it is trusted.
What really happensagent-evaluation builds a dataset, runs the evaluation and reports results so fixes can be measured.
Mirage Djinn takes 14. Summoner: Ward. Mirage Djinn falls.
The Mirage Djinn falls.
Claude Code and Codex
npx skills add mlflow/skillsSkills include instrumenting-with-mlflow-tracing (Python and TypeScript, OpenAI, Anthropic, LangChain and more), analyze-mlflow-trace, debug-agent, agent-evaluation, build-a-scorer and querying-mlflow-metrics. An optional UserPromptSubmit hook suggests a skill from your prompt. Also listed as mlflow@claude-plugins-official. Written for MLflow 3.8 or later.
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