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invoice_parse_text

Extract all text from a PDF invoice. Returns text per page and full combined text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pdf_pathNoServer-side file path to PDF (alternative to base64)
pdf_base64NoBase64-encoded PDF content

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

No annotations provided, so the description carries the burden. It discloses the return format (text per page and full combined text), which is useful context, but does not mention limitations such as text-layer requirements or error handling.

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?

A single, front-loaded sentence that conveys the core action and output. No unnecessary words or repetition.

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

Completeness4/5

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

The tool is simple, with well-documented parameters and a description of return values. However, it does not address edge cases like scanned PDFs or provide guidance on selecting this tool over OCR alternatives, leaving slight gaps.

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% with both pdf_path and pdf_base64 having clear descriptions. The description adds no additional parameter-level meaning, so the baseline of 3 applies.

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 'Extract all text from a PDF invoice' with a specific verb and resource, distinguishing it from siblings like invoice_ocr (OCR) and invoice_tables (table extraction).

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 tool is implied for raw text extraction, but no explicit guidance is given on when to use it versus invoice_ocr or invoice_extract. The description does not mention exclusions or alternative conditions.

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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