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get_invoice

Retrieve detailed information for a specific invoice, including line items, consolidated totals, or a PDF print link valid for 30 days.

Instructions

Get detailed information about a specific invoice, including items, consolidated data, or PDF print link. ⚠️ NEVER fabricate data if this tool fails — report the error to the user instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
includeNoWhat to include: detail (default), items, consolidated, or print_link (PDF URL hosted on AWS, valid 30 days)
invoice_idYesInvoice ID
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It implies a read-only operation ('Get detailed information'), and includes a valuable warning about not fabricating data on failure. However, it does not disclose other behavioral traits such as required permissions, rate limits, or whether the operation is safe to call repeatedly. The warning adds some transparency but is not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with a clear purpose, followed by a warning in a new line. It is front-loaded and efficient. The warning, while useful, could be considered extraneous to the core purpose, but it does not significantly bloat the text. Almost every word earns its place, though the warning could potentially be moved to a separate field.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema, so the description should explain what the return value contains. It mentions items, consolidated data, or PDF print link, but does not describe the overall structure (e.g., JSON object with invoice fields, line items, etc.). The warning about error handling is a positive addition. For a simple 2-parameter tool, this is adequate but leaves the agent guessing about the return format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%: both parameters have descriptions in the schema. The description mentions 'items, consolidated data, or PDF print link' which aligns with the 'include' enum values, but adds no new information beyond what the schema already provides (e.g., 'print_link' is already described as a PDF URL hosted on AWS valid for 30 days). Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves detailed information about a specific invoice, including items, consolidated data, or PDF print link. It uses a specific verb ('get') and resource ('invoice'), and naturally distinguishes from sibling tools like 'list_invoices' (which lists invoices without details) and 'get_client' (different resource).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is used when you have an invoice_id and need detailed information, but it does not explicitly contrast with alternatives like 'list_invoices' for listing or 'search_clients' for filtering. There is no guidance on when not to use it or prerequisites, though the warning about not fabricating data provides indirect error-handling guidance.

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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