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

Annotations already provide readOnlyHint=true. The description adds that it returns a 'structured, audited deliverable' and that inputs are 'validated server-side', which is useful context. But it doesn't disclose output structure, pagination, rate limits, or async behavior beyond what the schema hints.

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 contains a promotional tagline ('Gapup agent-payable C-suite expertise (RISK)') and a long reference case. While bulleted, it is not front-loaded and includes sentences that add little value, such as the vague 'RISK' label and the closing validation note.

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 8 parameters, no output schema, and only minimal annotations, the description omits key usage details: how to specify the exact focus, what the deliverable contains beyond vague 'GRADE rating', and how async polling works. The reference case helps but is not a substitute for explicit guidance.

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 only 13%. The description maps some placeholders (e.g., 'drug/intervention', 'indication') but never explains max_studies, date_range_years, intervention_type, or async. It fails to compensate for the sparse schema for most parameters.

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 states it produces a 'Brief évidence clinique (GRADE)' and enumerates specific question types (efficacy, safety, comparative effectiveness, repurposing, evidence gaps). This is a specific verb+resource with distinct scope, distinguishing it from siblings like clinical_pharma_intel or sci_literature_search.

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 example questions clearly imply when to use the tool (e.g., for GRADE ratings, safety signals, comparative effectiveness). However, it never explicitly names alternatives or exclusion criteria, so it stops short of full when/when-not guidance.

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