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mlflow-mcp-server

log-batch

Log multiple metrics, parameters, and tags to an MLflow run in a single batch operation, reducing the number of API calls needed.

Instructions

Log a batch of metrics, params, and tags to a run

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
runIdYes
metricsNo
paramsNo
tagsNo
Behavior2/5

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

Annotations indicate non-read-only but description adds no behavioral context (e.g., overwrite behavior, error handling, rate limits). Minimal value beyond annotations.

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?

Single concise sentence with no redundancy or unnecessary detail.

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

Completeness3/5

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

Adequate for a straightforward batch logging tool but lacks info on run existence, idempotency, or return values (no output schema).

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 coverage 0% and description only lists parameter categories (metrics, params, tags) without explaining required fields or format. Fails to compensate for schema gaps.

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?

Description clearly states the verb 'log', resource 'a batch of metrics, params, and tags', and destination 'to a run'. It distinguishes from singular logging siblings.

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?

No explicit guidance on when to use batch vs individual logging. Siblings like log-metric and log-param exist but no comparison 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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