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mlflow-mcp-server

log-metric

Log a metric value to an MLflow run by specifying metric name, value, and run ID. Optionally include timestamp and step.

Instructions

Log a single metric value to a run

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
runIdYes
keyYesMetric name
valueYesMetric value
timestampNoUnix timestamp ms (defaults to now)
stepNoStep at which metric was recorded
Behavior2/5

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

Annotations indicate mutation (readOnlyHint=false) and potential side effects (openWorldHint=true), but the description adds no further behavioral context such as whether duplicate metrics overwrite or append, or what side effects occur.

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 sentence front-loads the core purpose with no extraneous words.

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?

Lacks critical details about metric insertion behavior (overwrite vs append), error handling, and return values. For a mutation tool with side effects, this is insufficient for an agent to use correctly.

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 describes 4 of 5 parameters (80% coverage). The tool description does not add any additional meaning beyond the schema, including for the undocumented runId parameter. Baseline is 3 per schema coverage.

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 (log), the object (a single metric value), and the target (to a run). It effectively distinguishes from sibling tools like log-batch which logs multiple metrics.

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 over alternatives such as log-batch for multiple metrics or log-param for parameters. The description does not specify prerequisites or conditions.

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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