corpus_stats

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that the tool returns rows and schema, which is useful but superficial; it does not disclose potential error behavior, auth needs, or performance implications. Since the annotations carry most of the burden, the description adds moderate value.

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, front-loaded sentence with zero fluff. It immediately states what the tool does and the scope, making it easy for an agent to parse quickly.

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 read-only operation with one parameter and an existing output schema, the description is adequate. It defines the tool's function and scope without leaving major gaps. It does not mention edge cases (e.g., what happens if the corpus key is invalid) but those are minor given the tool's simplicity and the presence of an output schema.

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 fully documents the sole parameter (corpus: 'Variant key.') with 100% coverage. The description does not add any parameter-specific meaning, so the baseline score of 3 applies—the schema already does the heavy lifting.

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 states a specific action (“Return”) and resource (“rows and schema for exactly one declared dataset configuration”), which clearly distinguishes it from siblings like list_corpora (which lists datasets) and search_segments (which searches within data). The phrase 'exactly one' further narrows the scope, making the tool's purpose unambiguous.

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—when you need both the data and structure of a specific dataset configuration—but it does not explicitly state when to choose this tool over alternatives, nor does it mention any exclusions. The usage context is inferable but not spelled out.

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