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

Annotations already cover read-only, idempotent, non-destructive, and open-world hints. The description adds valuable context beyond annotations: it specifies the data source (eutils.ncbi.nlm.nih.gov), the public domain nature, and the fact that the query translation NCBI actually ran is returned. This provides behavioral transparency about the data provenance and the nature of the response, which is not present in the annotations.

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 concise and well-structured. It front-loads the action and purpose, provides examples, states the return values, and then gives a short data provenance note. Each sentence adds essential information without redundancy. There is no fluff, making it easy 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 search tool with a full input schema and an output schema present, the description is complete. It tells the agent what to input, what to expect as output, how to use the result (with siblings), and notes auth requirements. Nothing essential is missing for an agent to correctly invoke and use 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?

The input schema covers both parameters thoroughly: 'query' has a description with examples and 'retmax' has range and default details. The description adds no new meaning beyond what the schema already provides; it merely reiterates that query can be scientific or common name, which is already in the schema. With 100% schema coverage, the description does not need to compensate, so a 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 states a specific action (search), the resource (NCBI Taxonomy database), and the input (scientific or common name) with examples. It also clarifies the output (TaxIDs plus query translation) and differentiates from sibling tools by specifying that the returned tax_id is used with taxonomy_summary or taxonomy_lineage, so the agent knows exactly what this tool does and how it relates to others.

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 explicitly mentions the follow-up tools (taxonomy_summary, taxonomy_lineage) and tells the agent to use the returned tax_id with them, which implies when this tool is appropriate. It also states no auth is required, which sets expectations. However, it does not explicitly state situations where this tool should not be used or why it might be preferred over other search tools, so a small gap remains.

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