How do I install the Searching Mlflow Docs skill?

Run npx skillmds@latest add mlflow/searching-mlflow-docs in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Searching Mlflow Docs safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Searching Mlflow Docs?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Searching Mlflow Docs free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Searching Mlflow Docs?

mlflow (@mlflow) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Searching Mlflow Docs by mlflow — Agent Skill

Name: Searching Mlflow Docs
Rating: 4.2 (5 reviews)
Author: mlflow

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".

mlflow a6ca7aa 2.0 KB Updated Sep 9, 2026

File contents

MLflow Documentation Search

Workflow

Fetch https://mlflow.org/docs/latest/llms.txt to find relevant page paths
Fetch the .md file 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Do not use WebSearch — Always start from llms.txt; web search returns outdated or third-party content.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.

---name: searching-mlflow-docsdescription: 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".--- # MLflow Documentation Search ## Workflow 1. Fetch `https://mlflow.org/docs/latest/llms.txt` to find relevant page paths 2. Fetch the `.md` file at the identified path 3. 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.

Frequently asked questions