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

Annotations already declare this as a read-only, non-destructive, non-open-world operation. The description adds meaningful analytical behavior beyond that: it specifies the computed metrics, names scikit-allel and bcftools +fill-tags as sources, and calls out the exact Hardy-Weinberg test with an excess-heterozygosity tail.

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 front-loaded sentence that immediately identifies the tool's domain and then enumerates the statistics returned. It is dense but efficient, with no filler, though the long list of metrics and parenthetical sources makes it less scannable than a shorter structured summary.

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?

Given the complex statistical operation, rich 100%-covered input schema, and an output schema, the description supplies enough detail about what is computed and which populations can be selected. It does not explain limitations or sibling alternatives, but those gaps are less critical because the schema and output schema carry the structural burden.

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, group, groupBy, populations, _files, and _subject in detail. The description's phrase 'for all samples or one population' is useful but does not add much semantic detail beyond the schema's own parameter descriptions.

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 states a specific resource (a call set) and a precise set of per-site and per-sample genotype statistics, including allele counts, heterozygosity, F, and Hardy-Weinberg tests. It is clearly a population-genetics summary tool, though it does not explicitly distinguish itself from closely related siblings such as population_fst or variant_call_summary.

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 says statistics can be computed for all samples or one population, which clarifies scope, but it gives no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives like population_fst, population_ancestry, genotype_pca, or linkage_disequilibrium, leaving the agent to infer selection from the name alone.

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