diversity_kinship

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

With no annotations, the description carries the full burden, and it does a solid job: it discloses the mathematical formula, the side effect of writing 'kinship_matrix.csv', the reported values (most-related pairs and diagonal range), and the large-set performance strategy. It does not mention deeper caveats like memory usage, file overwrite behavior, or failure modes, but the core behavior is transparent.

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 compact and well-structured: definition, formula, outputs, then an important performance note. Every sentence contributes new information, and the most essential identity of the tool is front-loaded in the first sentence.

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?

The description covers the core behavior, outputs, and a key performance consideration, and an output schema apparently exists to handle return-value details. It is slightly incomplete because it lacks explicit guidance about when to choose kinship analysis over related diversity/QC modules, but for invoking the tool with correct parameters it is sufficiently complete.

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 already documents all parameters at 100% coverage, so the baseline is 3. The description adds real value beyond the schema by explaining why 'method' and 'max_markers' matter together ('avoid a full VCF export') and by framing the input as 'alt dosage', which helps parameter interpretation. This raises the score above baseline.

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 clearly names the resource ('VanRaden genomic relationship (kinship) matrix'), states the computation ('Computes G = ZZ'/(2 Σp(1-p)) from alt dosage'), and specifies concrete outputs. It is specific enough to distinguish from most siblings, but it does not explicitly differentiate itself from closely related diversity_* or QC tools.

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 practical configuration guidance ('For large sets pass method="allelematrix" + max_markers to avoid a full VCF export'), but it never states when a user should choose this tool over siblings like diversity_pca, diversity_fst, or qc_duplicate_accessions. Usage context is implied by the kinship focus rather than made explicit.

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