Taxonomy Ncbi Search

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

Goes well beyond the readOnly/openWorld/idempotent annotations by disclosing that modified_since is not applied server-side and that filtering happens in the adapter, plus the exact comparison used. That is exactly the kind of non-obvious behavior an agent cannot get from annotations or schema.

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 core purpose and its query example are front-loaded in one sentence, and the caveat follows immediately. Some redundant framing around the 'source-adapter checkpoint contract' could be trimmed, but it earns most of its length.

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?

An output schema exists so return values needn't be described, and the tricky modified_since behavior is covered. However, with four parameters at zero schema coverage, the pagination parameters remain unaddressed, leaving a real gap for correct invocation.

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%, so the description must compensate. It explains 'term' via example and gives deep semantics for 'modified_since', but retmax and retstart are left completely undocumented in both schema and description.

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?

States a specific verb and resource ('Search NCBI Taxonomy') and gives a concrete Entrez query example, which distinguishes it from the sibling GBIF search by naming the data source. It stops short of explicitly contrasting with taxonomy_gbif_search.

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 example query syntax implies how to use it, but there is no guidance on when to choose this over taxonomy_gbif_search or gbif_occurrence_search, nor any stated prerequisites. Usage is inferable rather than explicit.

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