Get Protein GO Terms

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

Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds that it 'always returns `count` and `count_by_aspect`' and details evidence fields, enhancing transparency without contradiction.

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?

A single sentence packed with essential information, front-loaded with the main action, followed by structured details and a signature. No extraneous words.

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 3 parameters, existence of an output schema, and no nested objects, the description fully covers behavior, return structure, and parameter usage. It is complete for an AI agent to use correctly.

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 baseline is 3. The description adds value by explaining the 'token economy' for limit, grouping by aspect, and providing a signature example, elevating it to 4.

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 explicitly states 'Return Gene Ontology annotations for an entry, grouped by aspect...' with specific output fields (GO id, label, evidence ids). This clearly distinguishes it from sibling tools like get_protein or get_protein_features.

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 advises to 'pass `aspect` to scope to one ontology and `limit` to cap a large set (token economy),' providing clear usage guidance. It does not explicitly exclude scenarios but gives contextual advice.

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