purchase_documentPurchase the final document for a given draft. Returns a secure payment link to give to the user. After payment, the final PDF is emailed to the user within minutes. E-signature is not yet available.
| Name | Required | Description | Default |
|---|---|---|---|
| draft_id | Yes | ||
| customer_email | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations, the description discloses the return of a payment link, the email delivery of the final PDF within minutes, and that e-signature is not yet available. These are useful behavioral insights that go beyond the simple hints provided by annotations.
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 efficient, using four short sentences that front-load the main purpose and add relevant details (link return, email timing, e-signature limitation) without any redundant or vague wording.
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 simple purchase tool with two parameters and no output schema, the description covers the essential flow: purchase, payment link return, and post-payment email. It does not address error conditions or parameter edge cases, but those are not critical for a straightforward action.
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?
The schema has 0% description coverage, and the description does not explicitly explain draft_id or customer_email. It only hints at them through 'given draft' and 'to give to the user', leaving the agent to infer their exact roles and requirements.
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 clearly states the tool's purpose: 'Purchase the final document for a given draft.' It uses a specific verb and resource, and distinguishes itself from siblings like generate_document and get_document_status by focusing on the payment/purchase step.
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?
The description implies usage after a draft exists, and notes that it returns a payment link to give to the user, with the PDF emailed after payment. It does not explicitly name alternatives or exclusions, but the context is clear enough given the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool has a unique role in the document creation pipeline: list_document_types for discovery, get_requirements for gathering inputs, generate_document for drafting, purchase_document for buying, and get_document_status for tracking. No two tools overlap in purpose, minimizing misselection risk.
All tool names follow a consistent verb_noun snake_case pattern: generate_document, get_document_status, get_requirements, list_document_types, purchase_document. The verbs are clear and predictably structured.
Five tools is well-scoped for a legal document generation service, covering the essential workflow without unnecessary additions. The count feels natural for the domain and avoids bloat.
The tools cover the full user journey: discover available document types, fetch required questions, generate a draft, purchase the final document, and check order status. No critical step in the core workflow is missing, making the set functionally complete.