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

Annotations already flag destructiveHint and openWorldHint, but the description adds the concrete reason: it emails the user's name, work email and company to an external party, and the reply comes back to that address. It also discloses the non-idempotent consequence in practical terms ('each call sends a new request, so do not retry'), which annotations alone cannot convey.

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 tight sentences: what it does, what the side effect is, and the guardrails for calling it. The side-effect disclosure and the confirmation requirement are front-loaded where an agent will see them before acting.

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 10-parameter outbound-emailing tool with no output schema, the description covers the critical unknowns: external side effect, PII transmitted, reply channel, and no-retry semantics. It does not describe failure behavior or validation errors, but nothing essential to a correct call 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 description coverage is 100%, so every parameter's meaning, enum values, and conditional requirements (hours for volume, details for custom, datasets for pilot/volume) are already documented in the schema. The description only restates the PII fields being emailed and adds no syntax or format guidance beyond that, so baseline 3 applies.

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 ('Send a request to DataClue's sales team') and enumerates the four request types (samples, pilot, volume quote, custom collection). This clearly separates it from read-only siblings like get_pricing_and_terms or search_datasets.

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 an explicit precondition ('Only call this when the user has asked to contact DataClue and has provided their own work email'), a confirmation step ('show them the details to confirm before sending'), and a retry rule ('do not retry a successful call'). Both when-to-use and when-not-to-act are spelled out.

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