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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read-only operation. The description adds modest behavioral context by noting the tool returns specific fields (taxon name, authorship, rank, status, source dataset) and that it is a single-record fetch, but it does not describe any hidden behaviors such as rate limits or error handling. With annotations covering the safety profile, the description's additional contribution is limited, making 3 appropriate.

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 a single sentence that is front-loaded with the core verb and resource, then adds the return fields and usage context. It packs all essential information without redundancy or filler words. Every phrase earns its place, making it concise and well-structured.

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 essential aspects of the tool: what it does, how to invoke it (by COL ID), what it returns, and its place in the workflow (after search/name_match). An output schema exists, so return values are further specified there. No additional context like pagination or authentication is needed for a single-record read-only fetch. The description is complete for the tool's complexity.

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 for missing parameter details. It does so by clarifying that 'id' is the COL ID and implicitly tying 'dataset' to the 'source dataset' in the return fields. This gives the agent enough meaning to understand the role of both parameters, though it could be more explicit about the format of 'id' or optionality of 'dataset'. Given the low coverage, this is solid compensation, but not perfect, so a 4 is warranted.

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 uses a specific verb ('Fetch') and resource ('single Catalogue of Life name-usage record') and identifies the key lookup mechanism ('by its COL ID'). It also distinguishes from sibling tools like 'search' and 'name_match' by emphasizing it retrieves the full structured record after those preliminary steps.

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 states when to use the tool: 'Use after search or name_match to retrieve the full structured record.' It provides clear context for the typical workflow, but does not explicitly mention when not to use it or list alternative tools beyond the implicit pipeline. This is strong guidance but lacks explicit exclusions, so it falls short of a 5.

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