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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered; the description earns credit for adding real behavior beyond that. It discloses that the tests are fixed in advance and executed in a fixed order against two public tables, which tells the agent the procedure is not user-configurable. It does not say what the terminal outcomes look like (supported/rejected/inconclusive across the sequential steps), which keeps it from a 5.

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?

A single tight sentence with the hypothesis form front-loaded ahead of the mechanism. It is dense but has no redundant wording; the only cost is that 'POPPER-style' consumes space an agent may not parse.

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 9-parameter tool with nested objects and an output schema, the description covers the core operation but omits how the two table-based tests are selected or interacted with (expression_test, tissues vs trait_genes, categories). Because an output schema exists, return values need not be explained, and the safety annotations are supplied, so the remaining gap is moderate rather than severe.

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 gene, alpha, kappa, categories, tissues, trait_genes and expression_test. The description's only added signal is 'two public tables', which loosely maps the expression test and the association-category test but adds no syntax or format detail. Baseline 3 is appropriate 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?

States a specific verb+resource: it runs a gene-trait hypothesis ("gene G is involved in trait T") through sequential falsification against two public tables. That clearly distinguishes it from catalogue-style siblings such as gene_set_enrichment or rank_next_tests. It stops short of a 5 because 'POPPER-style sequential falsification' is jargon that an agent must already understand to grasp the operation.

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 hypothesis form ("gene G is involved in trait T") implicitly tells the agent when this tool applies, but there is no explicit when-to-use versus when-not-to-use guidance. No alternative tool is named for a related need, e.g. ranking candidate tests with rank_next_tests or testing gene-set membership with gene_set_enrichment.

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