get_sample_metadata

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

The description adds critical behavioral context beyond the readOnlyHint and openWorldHint annotations: it explicitly states that the tool is not implemented in this build and will return error code 'unsupported' (E6, E7). It also clarifies that values are returned exactly as supplied by the source, which is useful non-obvious behavior.

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?

Two short sentences, each carrying essential information. The primary purpose is front-loaded, and the unsupported-status warning is placed second without unnecessary elaboration.

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?

The description covers purpose and the critical unsupported behavior, and an output schema exists. However, the complete lack of parameter semantics and absence of usage guidance leave meaningful gaps for an agent deciding whether and how to call this 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%, and the description does not explain what 'source' or 'accession' mean, what formats are expected, or how they relate to the metadata lookup. The description adds no parameter-level meaning beyond the raw 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 identifies the operation: retrieving one sample's metadata and phenotype values as supplied by the source. It is specific enough to distinguish from list_samples, but it does not explicitly name or differentiate sibling tools.

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 about when to use this tool versus alternatives such as list_samples or describe_dataset. The 'not implemented' warning is behavioral, not usage guidance.

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