Assign a tag to an MLflow run to annotate it for review or mark the best model. Use run ID, key, and value to add metadata.
Set a tag on a run (e.g. annotate best model, flag for review).
Args: run_id: The run ID to tag. key: Tag key, e.g. 'best_model', 'reviewed_by'. value: Tag value.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | ||
| value | Yes | ||
| run_id | Yes |
Changes observed during successful MCP inspections.
v0.4.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate idempotentHint=true and readOnlyHint=false. The description adds no behavioral traits beyond what the name and annotations convey (e.g., no mention of overwrite behavior or side effects).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with a clear Args section. It is front-loaded, concise, and every sentence is useful without unnecessary repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple, the description lacks details on what happens on success (e.g., return value) and whether tags are overwritten or appended. However, given the idempotentHint and no output schema, the description is adequate but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description repeats parameter names with minimal elaboration and provides examples for the 'key' parameter (e.g., 'best_model', 'reviewed_by'), adding moderate value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Set a tag on a run') with concrete examples ('best model', 'flag for review'), and the name and context distinguish it from sibling tools like set_experiment_tag and set_registered_model_tag.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly limits usage to runs and provides examples, but does not explicitly state when to use this tool versus alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.