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mlflow-mcp-server

by us-all

get-experiment

Retrieve details of an MLflow experiment using its experiment ID. Optionally extract specific fields to reduce response size.

Instructions

Get experiment details by ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
experimentIdNoExperiment ID (defaults to MLFLOW_EXPERIMENT_ID)
extractFieldsNoComma-separated dotted paths with `*` wildcard (e.g. 'experiments.*.experiment_id'). Reduces response tokens.
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description should disclose behavioral traits. It only says 'Get experiment details' without mentioning read-only nature, potential errors, or any side effects. The behavioral transparency is minimal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that directly states the purpose. It is concise and front-loaded with no extraneous words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 required params, no output schema), the description is largely sufficient. However, it could be more complete by mentioning what is included in 'experiment details' (e.g., tags, parameters, metrics).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides descriptions for both parameters with 100% coverage. The tool description adds no additional parameter meaning beyond what the schema states, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (get) and the resource (experiment details) along with the identifier (by ID). It distinguishes itself from sibling tools like 'get-experiment-by-name' which uses a different identifier.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when you have an experiment ID, but does not explicitly guide when to use this tool versus siblings like 'get-experiment-by-name' or 'search-experiments'. No when-not-to-use or alternative guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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