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

Annotations already declare the write/safety profile (readOnly=false, destructive=false, openWorld=false, non-idempotent), so the description's real contribution is telling the agent this files into a 'verification queue' — implying human review rather than an immediate fix. It does not say what happens after review or whether duplicate reports are merged, which would complete the picture.

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?

Three short sentences, front-loaded with the action and destination. There is slight redundancy between the parenthetical examples and 'when our data looks wrong', but nothing is wasted at length.

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?

With an output schema present, return values need no explanation, and annotations cover safety. The description is complete enough to call the tool correctly; only post-submission behavior (queue turnaround, deduplication) is left out.

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 75%, so the schema carries most of the burden. The description's issue examples loosely map to the 'pricing'/'status'/'feature' enum values, adding some interpretive value, but it says nothing about the 'claim' or 'evidence_url' semantics.

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 and resource ('Report a data problem') and gives concrete examples (wrong price, dead tool, missing feature), plus the destination ('Toolradar verification queue'). It is clearly distinct from the read-only siblings like get_tool or compare_tools, though it never names them.

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?

'Use this when our data looks wrong so we can fix it' gives an explicit trigger condition, and the examples sharpen it. No exclusions or named alternatives are offered, but for a single intake tool among pure lookups there is little ambiguity to resolve.

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