diversity_core_collection

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

With no annotations, the description carries the full burden and does well: it discloses the greedy algorithm, that it writes core_collection.csv with specific columns, and that it reports captured allelic diversity. It doesn't discuss overwrite behavior or computational cost, but the main behavioral contract is clearly stated.

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?

Three concise sentences with no filler: purpose, algorithm, selection modes, and output are all front-loaded. Every sentence earns its place and the structure is 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?

For a computational analysis tool with a rich 7-parameter schema and an output schema available, the description covers the key context: goal, method, selection modes, and output artifact. It does not walk through method/region/max_markers, but those are fully documented in the schema, so the description does not need to repeat them.

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 100%, so the baseline is 3. The description adds value beyond the schema by explaining the relationship between size and fraction and noting the default 10% fraction, which reinforces the schema's default and clarifies the intended usage.

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 ('Select a core collection that maximises captured allelic diversity') and goes on to name the greedy allele-coverage algorithm, which clearly sets it apart from sibling diversity_* tools that perform PCA, kinship, FST, etc. It also specifies the two selection modes (size vs fraction), leaving no ambiguity about what the tool does.

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 implies when the tool is appropriate (whenever a core collection maximizing allelic diversity is needed) but does not explicitly state when to prefer it over alternatives or when not to use it. It gives no exclusions or comparison with the many other diversity_* siblings, so the usage context is only implicit.

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