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mlflow-mcp-server

log-logged-model-params

Log key-value parameters to a specific logged model for tracking experiment metadata.

Instructions

Log parameters on a LoggedModel

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelIdYes
paramsYesParams to log on the model
Behavior3/5

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

Annotations indicate it is not read-only; description confirms it's a write operation but adds no additional behavioral details (e.g., whether it overwrites or appends). Minimal added value.

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

Conciseness4/5

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

Single sentence, no fluff, but could be more informative while remaining concise.

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

Completeness2/5

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

Incomplete context: does not explain what a LoggedModel is, bulk behavior, or effect on existing parameters. With siblings present, more guidance is needed.

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

Parameters2/5

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

Schema has 50% description coverage; description adds no information about 'modelId' or the structure of 'params' beyond what the schema already provides.

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

Purpose4/5

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

The description clearly states it logs parameters on a LoggedModel, but does not differentiate from sibling tools like 'log-param' (singular) or 'log-batch'.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives (e.g., log-param, log-batch). The description only states what it does.

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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