get_experiment

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

No annotations are provided, so the description bears full burden. It discloses the returned data (metadata, config, metrics, notes) but does not mention side effects (likely none), authentication needs, or error behavior. It is adequate but not exhaustive.

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?

A single sentence of 9 words that immediately conveys the tool's purpose. No extraneous information, and the key components are listed efficiently.

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?

Given the simple nature (1 param, no output schema), the description covers the main return types. However, it lacks details on error handling, default behavior if no experiment exists, or whether the data is read-only. For a retrieval tool, it is sufficient but not fully comprehensive.

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?

The schema has one required string parameter (experiment_id) with no description. The tool description does not elaborate on the parameter beyond implying its role, offering no additional semantics or validation hints. Schema description coverage is 0%.

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 verb 'Return' and the resource 'full experiment detail', listing specific components: metadata, config, latest metrics, validator notes. This distinguishes it from sibling tools that may return partial data or different experiment aspects.

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 implies usage for retrieving comprehensive experiment details, but provides no explicit guidance on when to use this tool versus alternatives like get_experiment_results or validate_experiment. No exclusions or alternatives are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.