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

Annotations already cover safety (readOnly, idempotent, openWorld, non-destructive), so the bar is lower. The description adds genuine context beyond annotations: the provenance (published AI Search Index), the inclusion of data date, a public page and linked research findings, and critically the pooled-across-brands scope limitation. It does not mention rate limits or freshness cadence.

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?

Two sentences, front-loaded with the core action and resource, then the scope caveat. Dense but each clause carries information (source mix, shifts, citation behavior, provenance, date, links). Not padded.

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?

An output schema exists, so return values need not be explained, and the description focuses on what the tool covers plus a key scope limitation. Given a read-only index tool, this is nearly sufficient; the missing parameter guidance is the only notable 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?

Schema description coverage is 0% and the description never mentions the 'topic' or 'platform' parameters. With two undocumented enum parameters, the description should compensate but does not explain how the enums narrow the result or what combinations mean. The enum values are self-evident as strings but no semantic guidance is provided.

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 ('Show') and a well-defined resource: the mix of source types each AI platform cites, recent source shifts, and citation behavior, drawn from SurfacedBy's AI Search Index. This is clearly a platform-level landscape view. It does not explicitly name or differentiate from the sibling tools, keeping it from a 5.

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?

There is no explicit when-to-use or when-not-to-use guidance, but the scope caveat ('Rates are pooled across many brands and describe each platform, not any one business') implicitly signals that per-business questions belong elsewhere, e.g. inspect_page_evidence or analyze_answer_evidence. Usage remains inferred rather than stated.

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