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

Annotations already establish read-only, idempotent, and open-world behavior, so the description adds valuable detail on top: pagination limits (up to 100 children per call), return fields (taxon ID, scientific name, rank, status, higher classification), and the recommendation to use offset for large groups. This exceeds what annotations alone convey and is consistent with them.

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 efficient and well-structured, with the core purpose in the first sentence, followed by illustrative examples, pagination notes, ID acquisition guidance, and licensing/scope. Every sentence contributes unique information—no filler—and the structure flows logically from what the tool does to how to use it.

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?

For a simple listing tool, the description covers all necessary aspects: purpose, input acquisition, output contents, pagination strategy, and the scope of the data source (Catalogue of Life, ~10 million taxa across all kingdoms). It also mentions licensing (CC BY 4.0) and lineage, which is helpful. No critical information is missing.

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 input schema fully documents all three parameters (limit, offset, taxon_id) with descriptions and constraints, so the baseline is 3. The description adds meaningful context beyond the schema by advising where to obtain taxon_id (from sibling tools) and by giving a concrete example of when offset matters (e.g., Coleoptera with 400K+ species), which helps agents use parameters effectively.

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 precise statement of the tool's function: "List the immediate child taxa of a given taxon in the Catalogue of Life taxonomic tree." Concrete examples (family→genera, genus→species, order→families) make the purpose unmistakable and clearly differentiate it from sibling tools like search, suggest, and detail, which serve other purposes like finding taxa or getting details.

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 provides clear contextual guidance by indicating how to obtain the necessary taxon_id (from col.species.search or col.species.suggest) and by mentioning pagination with offset for large groups. However, it does not explicitly state when to choose this tool over alternatives beyond the col.* namespace, nor does it list exclusion criteria—slightly short of the 'explicit when/when-not' standard.

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