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extract_information

Extract key information from documents using a user-defined schema or auto-generation. Handles PDFs, images, and Office files up to 50MB.

Instructions

Extract structured information from documents using Upstage Universal Information Extraction.

This tool can extract key information from any document type without pre-training.
You can either provide a schema defining what information to extract, or let the system
automatically generate an appropriate schema based on the document content.

Supported file formats: JPEG, PNG, BMP, PDF, TIFF, HEIC, DOCX, PPTX, XLSX
Max file size: 50MB
Max pages: 100

Args:
    file_path: Path to the document file to process
    schema_path: Optional path to a JSON file containing the extraction schema
    schema_json: Optional JSON string containing the extraction schema
    auto_generate_schema: Whether to automatically generate a schema if none is provided

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesPath to the document file to process
schema_jsonNoJSON string containing the extraction schema (optional)
schema_pathNoPath to JSON file containing the extraction schema (optional)
auto_generate_schemaNoWhether to automatically generate a schema
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses supported file formats, maximum file size (50MB), and maximum pages (100), which are useful constraints. However, it does not mention whether the operation is read-only, what happens on failure, or any rate limits. Given that the tool is non-destructive, the transparency is adequate but 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.

Conciseness3/5

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

The description is reasonably structured with a brief intro followed by bullet points for constraints and a list of arguments. However, it is somewhat verbose, especially the 'Args' section which duplicates the input schema. Not all sentences earn their place; the 'without pre-training' phrase is extraneous.

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

Completeness2/5

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

Given the tool has 4 parameters, no output schema, and no annotations, the description should cover output format and error behavior. It does not explain what the extracted information looks like or how to interpret the result. It also does not mention any prerequisites (e.g., valid document content) or edge cases, leaving significant gaps for the agent.

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 description coverage is 100%, so the baseline is 3. The description adds context that the schema can be provided via file path, JSON string, or auto-generated, which clarifies the relationship between the parameters. However, it largely repeats the schema descriptions without adding significant new meaning beyond explaining the optionality.

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

Purpose4/5

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

The description clearly states the tool extracts structured information from documents, using a specific technology (Upstage Universal Information Extraction). It mentions key capabilities like schema provision and auto-generation. However, it does not explicitly differentiate itself from the sibling tool 'parse_document', which could cause confusion about which tool to use for what.

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

Usage Guidelines2/5

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

The description explains the flexibility of providing a schema or auto-generating one, but it lacks guidance on when to use this tool versus its sibling 'parse_document'. There are no 'when to use' or 'when not to use' statements, nor prerequisites or context about the expected input document types.

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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