searching-mlflow-docs
Searches and retrieves MLflow documentation from the official docs site. Use when the user asks about MLflow features, APIs, integrations (LangGraph, LangChain, OpenAI, etc.), tracing, tracking, or requests to look up MLflow documentation. Triggers on "how do I use MLflow with X", "find MLflow docs for Y", "MLflow API for Z".
- Installs
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/mlflow/skills --skill searching-mlflow-docs- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads searching-mlflow-docs automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
MLflow Documentation Search
Workflow
- Fetch
https://mlflow.org/docs/latest/llms.txtto find relevant page paths - Fetch the
.mdfile at the identified path - Present results with verbatim code examples
Step 1: Fetch llms.txt Index
WebFetch(
url: "https://mlflow.org/docs/latest/llms.txt",
prompt: "Find links or references to [TOPIC]. List all relevant URLs."
)
Step 2: Fetch Target Documentation
Use the path from Step 1, always with .md extension:
WebFetch(
url: "https://mlflow.org/docs/latest/[path].md",
prompt: "Return all code blocks verbatim. Do not summarize."
)
Anti-Patterns
Do not use .html files — Fetch .md source files only.
Do not use WebSearch — Always start from llms.txt; web search returns outdated or third-party content.
Do not use vague prompts — "Extract complete documentation" allows summarization. Use "Return all code blocks verbatim. Do not summarize."
Do not use versioned paths — Always use /docs/latest/, never /docs/3.8/ or other versions unless the user explicitly requests a specific version.
Do not guess URLs — Always verify paths exist in llms.txt before fetching. Never construct documentation paths from assumptions.
Do not follow external links — Stay within mlflow.org/docs. Do not follow links to GitHub, PyPI, or third-party sites.
Do not mix sources — Use only MLflow docs. Do not combine with LangChain docs, OpenAI docs, or other external documentation.
Do not use llms.txt for non-GenAI topics — The llms.txt index covers LLM/GenAI documentation only. For classic ML tracking features, paths may differ.
FAQ
What does the searching-mlflow-docs skill do?
Searches and retrieves MLflow documentation from the official docs site. Use when the user asks about MLflow features, APIs, integrations (LangGraph, LangChain, OpenAI, etc.), tracing, tracking, or requests to look up MLflow documentation. Triggers on "how do I use MLflow with X", "find MLflow docs for Y", "MLflow API for Z".
How do I install searching-mlflow-docs?
Run npx skills add https://github.com/mlflow/skills --skill searching-mlflow-docs in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/searching-mlflow-docs/ (personal) or .claude/skills/searching-mlflow-docs/ (project).
Which AI agents can use searching-mlflow-docs?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is searching-mlflow-docs safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains searching-mlflow-docs?
It is published by mlflow in mlflow/skills. It has 1,059 recorded installs.
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