diversity_pca

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

No annotations are present, so the description carries the full burdens. It discloses preprocessing decisions (monomorphic markers dropped, missing mean-impured, Patterson scaling), output artifacts (pca_coords.csv, variance explained, outlier flags), and the trade-off between VCF export and allelematrix streaming. This is unusually 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?

Four compact sentences: purpose, algorithm and outputs, optional grouping, and large-set guidance. Every sentence earns its place and there is no restatement of schema fields.

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 10 parameters and no annotations, the description covers the core algorithm, outputs, optional metadata integration, and scale guidance. The rest of parameter meaning is fully supplied by the 100%-coverage input schema, and return values are covered by the output schema.

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 coverage is 100%, so the baseline is 3. The description adds coupling semantics: metadata_tsv + group_column together produce a group column for plotting, and method='allelematrix' + max_markers together avoid full VCF export. It does not describe region, id_column, or output_dir, but the schema already documents those completely.

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 'Principal component analysis of population structure' and immediately clarifies the mechanism: 'Runs PCA on the alt-allele dosage matrix'. This names a specific algorithm and resource, and the PCA framing distinguishes it from other diversity/structure tools like diversity_structure or diversity_kinship.

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?

It gives actionable conditional guidance: add metadata_tsv + group_column for group labelling/colouring, and use method='allelematrix' + max_markers for large sets to avoid full VCF export. No explicit when-not/alternative sibling routing is provided, but the practical usage context is clear.

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