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

Beyond the annotations, the description discloses the key behavioral facts: every submission enters a human review queue, nothing is published automatically, and a listing changes only after verification from a brand statement, official docs, reputable reporting, or a documented internal test. It also adds a privacy constraint about excluding personal data. It does not say what the tool returns (e.g., a submission identifier or queue status) or how duplicate submissions are handled, which matters given idempotentHint=false.

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 dense sentences, front-loaded with the enumeration of submission types and followed by the review/verification policy, with no filler. The parenthetical restatement of the enum values is slightly redundant with the schema, but it earns its place by giving each value a human-readable meaning.

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 14-parameter submission tool with no output schema, the description covers the workflow and evidence bar well but omits what happens after submission (return value, review latency, whether the submitter can track it) and does not clarify conditional parameter requirements per type. Those gaps are meaningful for an agent deciding whether to call it and how to fill the optional fields.

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?

The description explains the meaning of the `type` values in plain language and the evidentiary standard that motivates source_url and evidence_url, adding some meaning over the schema. But with 14 parameters at 64% schema description coverage, several fields (result, http_status, observed_at, submitter_role, proposed_status) receive no explanatory context in the description, and the conditional requiredness across types is only partially documented in the schema itself.

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 states a specific verb and resource ("Suggest a change to the database") and enumerates the four submission intents that map to the `type` enum, so an agent knows exactly what the tool does. It falls short of a 5 because it never addresses the sibling tool named report_block, which overlaps with the `report_block` submission type here, leaving the agent unable to distinguish the two paths from the description alone.

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 positive guidance by listing the four cases this tool covers (add_brand, correct_listing, report_block, report_works) and the verification standard required. However, it offers no exclusions and no routing advice relative to the siblings check_domain, check_domains, and especially report_block, so the agent must guess when a block report belongs here versus in the dedicated sibling tool.

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