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

With no annotations provided, the description carries the transparency burden. It explains that output is curated and intentionally short ('Keep the output short and focused'), mentions the types of data sources (GO, KEGG, UniProt Keywords), and discloses a limitation (no enrichment). It does not mention potential truncation details, but the schema parameter detail_for_term fills in that gap.

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 well-structured with a clear opening sentence, bullet points for usage, and an output field list. It is somewhat long but every section adds useful information; the front-loaded purpose statement makes it easy to scan.

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?

The description covers the tool's purpose, appropriate use cases, a key alternative, and detailed output fields. With an output schema present, it does not need to restate return types. It could mention the requirement for species, but the schema covers that, so overall completeness is strong.

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 tool description does not explain any of the three parameters by name or provide usage details. Schema description coverage is only 33%, and the description does not compensate by clarifying how to format identifiers, supply species, or use detail_for_term. The output field list is helpful but does not address parameter semantics.

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 opens with a specific verb and resource: 'retrieves curated functional annotations for a set of proteins.' It clearly distinguishes itself from sibling tools by explicitly stating it does not perform statistical enrichment and points to the enrichment tool for that purpose.

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 gives explicit when-to-use guidance: 'Use this when the user asks what a protein does, where it's localized, expressed, or which pathways it participates in.' It also provides an exclusion and alternative: 'This tool does not perform statistical enrichment — use the enrichment tool for that.'

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