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

Adds substantial behavior beyond the annotations: live saved rows that can go stale, pagination defaults (5, max 10), scanDate as a UTC calendar day or null, scanCompletedAt as exact finish time, subjectContext null for legacy scans, and a prompt-injection warning that raw text is evidence, not instructions. Annotations cover safety, but this adds real operational traits.

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?

Dense and mostly front-loaded, leading with the primary purpose, then filters, then pagination, then caveats. Every sentence carries information, though the density across multiple semicolon-joined clauses makes it slightly harder to scan than an ideal definition.

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?

Given 13 parameters, an output schema, and rich annotations, the description covers the critical mechanics: filtering, pagination/continuation, scan selection, and data-freshness caveats. Return-value content need not be explained since an output schema exists. Some filter parameter meanings remain unaddressed, leaving a small gap.

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?

With 46% schema coverage across 13 parameters, the description must compensate, and it does for the important ones: limit default/max, cursor continuation without changing filters, and omitting scanId on the first call to get the latest eligible Scan. Several filters (tag, stage, persona, product, category) still carry no meaning in either place, which keeps this below a 5.

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+scope: 'Read the full collected AI answers and per-brand metrics for one Scan.' It explicitly distinguishes itself from the sibling get_prompt_result_trends, which it names as the per-result history view, so an agent can route correctly without opening the schema.

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?

Gives clear operational context: narrow by promptId/platform/region, and use get_prompt_result_trends for per-result history. Continuation rules are spelled out. It does not explicitly state when this tool should be preferred over siblings like list_scans or get_visibility_overview, so it stops short of full when/when-not coverage.

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