Sample AI mention texts

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely new behavioral context — 'Dates must fall within the data retention window' — plus the limit bounds, which annotations cannot express. It stops short of describing pagination/return shape, so a 4 rather than 5.

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?

Front-loaded with what the tool returns, then alternatives, then constraints. Slightly dense with parenthetical asides, but every sentence carries real signal and nothing is filler.

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 12-parameter read tool with no output schema, the description covers purpose, filter dimensions, limit bounds, retention constraint and sibling routing. Gaps remain around sort semantics and date format, but nothing critical to correct invocation is missing.

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 coverage is only 25%, so the description must compensate. It documents the limit range and names the filter dimensions (engine, sentiment, mention type, competitor), but says nothing about sortBy, offset, or date format, leaving several of the 12 parameters documented in neither place.

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: 'Paginated sample of the raw AI mention texts themselves, for qualitative review and verifying sentiment labels.' It explicitly distinguishes itself from siblings get_sentiment_breakdown and get_mention_mix, so an agent can select it without opening other schemas.

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?

Explicit routing: 'Use to READ individual mentions. For the aggregate sentiment split use get_sentiment_breakdown; for the brand's own mention counts by type, tone and qualifier use get_mention_mix.' It also states the retention-window constraint and the limit range, leaving little to inference.

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