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".
How do I install this agent skill?
npx skills add https://github.com/mlflow/skills --skill searching-mlflow-docsIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The skill is a specialized tool for searching and retrieving official MLflow documentation from its primary website. It implements several security-minded constraints, such as restricting fetches to the official domain and preventing the agent from following external links or using untrusted search engines.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
- Runlayerpass
1/1 file flagged
- ZeroLeakswarn
1 finding · Score: 69/100
What does this agent skill do?
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Do not use WebSearch — Always start from llms.txt; web search returns outdated or third-party content.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.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/mlflow/skills/searching-mlflow-docs">View searching-mlflow-docs on skillZs</a>