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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds a useful return contract—reviewed vs unreviewed protein counts, lineage, common names—and shows query-to-ID resolution behavior with examples. It does not mention search matching semantics or rate limits, but the annotations plus simple schema reduce that burden.

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 compact and front-loaded with the purpose, then return fields, then usage context. The attribution sentence adds provenance without bloating the text. It is slightly longer than strictly necessary, but every sentence contributes useful information.

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 low parameter count, full schema coverage, existing annotations, and presence of an output schema, this description is complete. It gives purpose, return values, example mappings, and the downstream workflow context needed to invoke the tool correctly. Everything needed for correct selection and use is present.

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 coverage is 100%, so the schema already documents all three parameters clearly. The description adds concrete value by mapping example queries to actual taxon IDs (human → 9606, mouse → 10090, E. coli K12 → 83333), reinforcing how the query parameter should be used beyond the schema text.

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 a specific action—search UniProt taxonomy—and enumerates the exact resource outputs: taxon ID, scientific/common name, rank, lineage, and protein counts. The example mappings and reference to protein_search filtering help distinguish this taxonomy-resolution tool from the broader UniProt protein search/entry 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?

The description explicitly tells the agent when to use the tool: to resolve organism names to taxonomy IDs for protein_search filtering. It provides concrete examples but does not name alternative taxonomy sources or explicitly state when not to use this tool, so usage guidance is strong but not exhaustive.

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