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

Annotations only say readOnlyHint=false, openWorldHint=true, idempotentHint=false, and destructiveHint=false; the description goes far beyond that by disclosing exact credit costs per source, that failed searches are not charged, that runs are refused if the balance cannot cover them, and how to interpret 'fetched without rows' versus 'failed search.' This is precisely the behavioral context an agent needs beyond the annotation booleans.

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?

The description is long but every sentence contributes operational knowledge: pricing, failure modes, estimate flow, and rerun guidance. It is front-loaded with purpose, then moves through usage and cost. While it could be formatted as bullets, the density is appropriate for the tool's complexity.

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?

Given three nested parameters and no output schema, the description covers prerequisites, cost contingencies, failure semantics, and re-use via list_mentions. It explains what outcomes mean and when to use the estimate companion tool. No critical operational gap remains for an agent to call it 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?

Schema coverage is 100% and the schema already documents every parameter with descriptions. The description adds extra meaning around estimateToken (its 15-minute validity, that mismatched arguments are refused, and that it must come from explore_estimate after user approval) and clarifies that variable legs are billed on actual results, so quotes should be 'up to'. Because the schema carries the structural detail, the description's extra parameter context elevates it above baseline.

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 opens with 'Ask the Sources once, now, without creating a keyword, and read the mentions they return,' which states a specific verb, resource, and scope. It further differentiates from siblings by framing it as the way to test a discovery angle before creating a keyword, and by pointing to explore_estimate and list_mentions as counterparts. This leaves no ambiguity about what the tool does.

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 explicitly names the precondition 'Call explore_estimate first, show the person the total, and send its estimateToken only after they agree,' and gives an alternative for re-reading a run ('read it again with list_mentions kind="runs" run=<run.id> rather than running it twice'). It also frames the use case as testing before creating a keyword, which is a clear when-to-use. This is exemplary usage guidance.

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