update-experiment
Renames an experiment in MLflow by providing its ID and a new name.
Instructions
Rename an experiment
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| experimentId | Yes | Experiment ID | |
| newName | Yes | New experiment name |
Renames an experiment in MLflow by providing its ID and a new name.
Rename an experiment
| Name | Required | Description | Default |
|---|---|---|---|
| experimentId | Yes | Experiment ID | |
| newName | Yes | New experiment name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a write operation (readOnlyHint=false), and the description adds no further behavioral details like side effects, permissions, or constraints. It is adequate but not enhanced.
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 extremely concise (3 words) and directly states the purpose with no extraneous content. However, it may be overly minimal for some users but earns a high score for efficiency.
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?
For a simple rename operation with full schema and annotations, the description is adequate but lacks context about prerequisites (e.g., experiment must exist) or potential restrictions (e.g., cannot rename a running experiment).
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 coverage is 100% with clear parameter descriptions. The tool description adds no additional meaning beyond what the schema already provides, so baseline score of 3 is appropriate.
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 'Rename an experiment' clearly states the specific verb and resource, and distinguishes it from sibling tools like create-experiment, delete-experiment, and rename-registered-model.
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 is provided on when to use this tool versus alternatives, such as when to rename versus create a new experiment or delete an old one.
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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