diversity_fst

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool writes fst_pairwise.csv, explains that server-side BrAPI attributes are intentionally not used because the endpoint is unavailable on the target Gigwa build, and mentions caching behavior in the method parameter. These are meaningful behavioral details beyond the tool name, though it could also explicitly state whether any persistent state is modified.

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 well organized, front-loaded with the core purpose, and uses a compact bullet-like structure for the two group-definition paths. Every sentence contributes either to usage guidance, an example, or a behavioral caveat; there is no filler.

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 tool with 9 parameters and no annotations, the description covers the essential setup, outputs, grouping options, and a known server limitation. It also warns about the most likely mistake, misassembling variant_set_db_id, and points to sibling tools for metadata format. The presence of an output schema means the description need not enumerate return fields.

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?

Although the schema already covers 100% of parameters, the description adds substantial semantic value: it explains how groups_json and metadata_tsv interact, gives a working JSON example, clarifies the relationship between id_column and group_column, and provides a vivid warning about the variant_set_db_id format. This goes well beyond the raw schema 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 opens with a specific, informative phrase — 'Pairwise Weir & Cockerham Fst between groups of samples' — naming both the statistical method and the resource it operates on. It clarifies the grouping input formats, which distinguishes this from other diversity_* siblings by defining its exact analytical scope.

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 gives concrete guidance on the two acceptable ways to define groups, includes a JSON example, and references the metadata format used by import_metadata as a sibling touchpoint. It does not explicitly list when to choose this tool over diversity_by_group or diversity_summary, but it provides clear context for invoking it correctly.

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