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

Beyond the annotations (readOnly, idempotent, non-destructive, closed-world), it discloses that no AI model is called, no network access occurs, and answers are neither stored nor logged — meaningful trust and privacy context. It also sets expectations that the output is a fixed-template draft, not legal advice, and that omissions surface as bracketed placeholders.

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?

Purpose, inputs, defaulting behavior, and disclaimers are front-loaded in a dense block with no filler sentences. The downside is that it reads as one long run-on paragraph, making the gathering instructions harder to scan than a short bulleted structure would.

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 nine-parameter templating tool with an output schema, the description covers everything an agent needs: source of inputs, required vs optional, default handling, placeholder behavior, and the nature of the returned draft. Return-value detail is rightly delegated to the output schema.

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 already 100%, so parameters are documented, but the description adds operational meaning: only company_name is required, omitted answers become placeholders, and effective_date defaults to today (UTC). It does not restate the enum or item limits, which the schema already carries.

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 names a specific verb and artifact ("Builds a short AI use policy draft in Markdown"), states its size and structure (ten sections, about two pages), and explicitly derives its input from the sibling tool get_policy_questions, so an agent can tell exactly what this produces and how it differs from the sibling.

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 states the precondition (answers collected via get_policy_questions), the only required input (company_name), the behavior for missing answers (bracketed placeholders, listed in the result), and an explicit prohibition ("Ask the person for the answers, do not invent them"). That routes an agent correctly with no inference needed.

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