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

Annotations already declare read-only, idempotent, non-destructive, open-world behavior. The description adds meaningful non-annotation context: the demo-data caveat, separate clinical/assayed reporting, unique mutant samples, events/exclusions, hash and denominator preservation, and a private-compute platform note. It does not contradict the annotations.

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 front-loads purpose, discovery, and reporting constraints with no filler. However, several distinct instructions are packed into a few run-on sentences, making the structure less scannable than it could be.

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 complex seven-mode analysis tool, the definition covers discovery, the demo caveat, reporting semantics, and provenance preservation, and an output schema exists. It still leaves the agent to infer which analysis mode to choose from the schema's const values alone, a significant gap for this complexity.

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 reported at 100%, so the oneOf variants and their constraints already document valid inputs. The description adds only a single gene_profile example and generic reporting expectations; it does not explain what mutation_cohort, filter_cohort, compare, survival, co_occurrence, or top_mutated each mean beyond their const names.

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 verb and resource, 'Analyze an installed verified public study,' and names the bundled demo study plus the capabilities(source=study) discovery path. It does not explicitly distinguish this multi-mode analysis tool from siblings such as research or query_source, so it stops short of full sibling differentiation.

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 clear prerequisites, namely an installed verified public study, and a discovery step via capabilities(source=study), plus the caveat that ubi_synthetic is an invented demo. It does not name an alternative analysis tool or state when not to use this one, but the context is sufficiently clear.

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