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finance_ap_invoice_intake

Extract structured payable data from AP invoices - vendor, line items, GL codes, due dates, and detect anomalies like duplicates or off-contract items.

Instructions

Ingest an accounts-payable invoice (PDF, image, or email body) and extract a structured payable: vendor, line items, totals, GL coding, due date, payment terms, and any anomalies (duplicate, off-contract, amount drift). Args: message: Free-text objective for the action. invoice_url: Signed URL or platform artifact URI for the invoice file. invoice_text: Raw invoice text (alternative to invoice_url). expected_vendor: Optional vendor name to validate against.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNo
invoice_urlNo
invoice_textNo
expected_vendorNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Even without annotations, the description discloses key behaviors: it extracts a structured payable with anomaly detection (duplicate, off-contract, amount drift), accepts multiple input formats (PDF, image, email body), and provides alternative input methods (URL vs text). This adds significant context beyond input schema.

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

Conciseness5/5

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

The description is concise (two sentences plus bulleted Args) and front-loaded with the core purpose. Every sentence adds value, no redundancy. The Args section is clearly structured.

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

Completeness5/5

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

With an output schema available, the description need not detail return values. It covers input formats, extraction fields, anomaly detection, and optional validation, making it complete for an intake tool without gaps.

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

Parameters5/5

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

Despite 0% schema description coverage, the description fully explains each parameter: 'message' as free-text objective, 'invoice_url' as signed URL/artifact URI, 'invoice_text' as raw text alternative, and 'expected_vendor' as optional validation. This compensates completely for the missing schema descriptions.

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 verb 'ingest', the resource 'accounts-payable invoice' (PDF, image, or email body), and the output: a structured payable with vendor, line items, totals, GL coding, due date, payment terms, and anomalies. This distinguishes it from sibling tools like xero_intake_invoice by specifying the extraction detail and anomaly detection.

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 usage for AP invoice ingestion but does not explicitly state when to use this tool vs alternatives like xero_intake_invoice or create_bill tools. No prerequisites or exclusions are mentioned, so the agent must infer context from the tool's purpose.

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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