Harvest quotable customer language

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

Annotations already mark the tool read-only and non-destructive. On top of that, the description discloses important behavior: results are verbatim, carry permalinks for citation, and are tagged by intent. This goes beyond what annotations alone tell an agent.

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?

Four sentences, all purposeful: what it does, when to use it, what output looks like, and what intents mean. Non-needed details are absent and key usage guidance is front-loaded.

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 an 8-parameter read-only tool with a fully documented schema and no output schema, the description provides the key missing context: return value shape, citability, and intent taxonomy. An agent has enough to call and interpret the tool correctly.

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?

Input schema covers 100% of parameters with descriptions, so the schema carries the parameter semantics. The narrative adds overall context about intents and verbatim output but no parameter-level details beyond the schema.

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?

Opens with a specific verb and resource: 'Research a topic and return only the quotable sentences, tagged by intent.' It adds the distinguishing constraint 'only the quotable sentences' and names the exact output shape, which separates it from broader research or browsing siblings even without naming one.

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 explicit when-to-use guidance: 'Use this when the goal is customer language: the exact words people use about a problem, a want, or an objection.' It does not name alternative tools or state when not to use it, but the context is clear enough for an agent to select it appropriately.

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