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

Annotations already carry the safety profile (readOnly, non-destructive, closed-world). Beyond that, the description discloses genuinely non-obvious behavior: results are produced per site AND averaged with a block-jackknife standard error, all pairs are enumerated when more than two populations are given, and it states the tool was validated on 1000 Genomes phase 3 APOL1. That added context exceeds what the annotations provide.

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 core purpose is front-loaded in the first clause, with method and scope details following in order of relevance. It is dense and somewhat run-on, and the trailing validation sentence is ancillary, but overall it is appropriately sized with little waste.

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?

With an output schema present, return values need not be explained, and annotations cover the safety profile. The description supplies estimator behavior and scope adequately for correct invocation, though it omits practical prerequisites (e.g. what sample-table columns are expected, genotype ploidy handling) that the schema only partially conveys.

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 schema already documents vcf, compare, groupBy, populations, estimator, and blockLength in detail. The description reinforces that every pair is compared when >2 populations are supplied, but adds little parameter-level syntax or format meaning beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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 names a specific analytic operation ('Differentiation between populations of a call set') plus the concrete statistics computed (Weir-Cockerham θ, Hudson's/Patterson's Fst). An agent can tell this is a population-genetics Fst tool, not a generic stats or ancestry tool. It does not explicitly differentiate itself from close siblings such as population_site_stats, population_ancestry, or genotype_pca.

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?

Usage is only implied: it notes θ applies 'over two or more populations' and Hudson/Patterson work 'between pairs', which hints at estimator selection, but there is no explicit when-to-use/when-not guidance, no prerequisites (e.g. genotype-only VCF, ploidy 2), and no named alternatives. An agent must infer context from the schema's minimum requirements.

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