Assign a key-value tag to an MLflow experiment to organize and annotate it with custom metadata.
Set a tag on an experiment.
Args: experiment_id: The experiment ID to tag. key: Tag key, e.g. 'team', 'status'. value: Tag value.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | ||
| value | Yes | ||
| experiment_id | Yes |
Changes observed during successful MCP inspections.
v0.4.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate idempotentHint=true (safe to repeat) and readOnlyHint=false (mutation). The description 'set a tag' implies overwriting behavior, but no additional detail is provided (e.g., limits, side effects). Annotations already supply key behavioral info.
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?
Short and to the point, but the 'Args' section essentially duplicates the schema. Could be more concise by omitting argument descriptions that add no new information.
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?
No output schema and high parameter count (3) with 0% coverage. The description does not clarify return value, overwrite behavior, or any prerequisites. Incomplete for a mutation tool.
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%, so the description must compensate. It provides examples for key ('team', 'status') but no type constraints or default values. Minimal added meaning beyond parameter names.
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 tool sets a tag on an experiment and lists parameters. However, it does not differentiate from sibling tools like set_run_tag or set_registered_model_tag, which serve similar purposes for different entities.
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?
No guidance on when to use this tool versus alternatives (e.g., set_run_tag for runs, set_registered_model_tag for models). The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.