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

Annotations already declare this is a write (readOnlyHint=false), non-idempotent, non-destructive, closed-world operation. The description adds the things annotations cannot: it consumes 1 AI credit per batch, needs user confirmation, and produces drafts requiring human review. It stops short of explaining what happens on partial failure or what the returned payload looks like.

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 short sentences, each carrying distinct information: what it does, what it costs and the confirmation prerequisite, and the human-review requirement. Nothing is redundant and the core action 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?

With no output schema, the description could say more about the shape of the returned drafts (e.g. per-question answers, confidence, or error on exceeding 6). Apart from that, everything an agent needs to invoke this correctly — inputs, cost, confirmation step, review responsibility — is present.

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 50%: application_id is documented in-schema as coming from tailor_application or list_my_applications, while the questions array has no schema description. The description compensates by explaining that questions are drawn from a job's application form and that they are capped at 6, matching the maxItems constraint.

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 (drafts) and resource (answers to a job's application form), plus scope limits (up to 6 questions) and grounding ('using the user's real experience'). This clearly distinguishes it from sibling tools like tailor_application, which operates on the CV side of the workflow.

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 for invocation ('confirm with the user first' due to credit cost) and a post-condition ('the user should check and edit the answers before using them'). It does not name alternatives or state when not to use it, so it falls just short of a 5.

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