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mlflow-docs

mlflow-docs

github.com/mlflowOther8217 installsUpdated 2d ago
Repository

About mlflow-docs

mlflow-docs is a skill for retrieving MLflow documentation on a specified topic. It uses the documentation index to locate Markdown sources and presents code examples verbatim.

Key features

  1. 01Searches the MLflow llms.txt index
  2. 02Fetches verified Markdown pages
  3. 03Preserves code examples verbatim
  4. 04Restricts sources to MLflow documentation

Use cases

  1. 01Find current documentation for an MLflow topic
  2. 02Retrieve code examples from official docs

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/mlflow/skills --skill mlflow-docs

After installing, type/mlflow-docsin Claude Code to confirm it loaded.

Details

From the project README

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Do not use WebSearch — Always start from llms.txt; web search returns outdated or third-party content.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.

Comments

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