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Document splitting

parserail_split

Classify and split multi-document bundles into individual documents, identifying boundaries and generating summaries.

Instructions

A multi-document scan bundle classified and split: what each document is, where it starts and ends, and a summary. Costs credits from the account wallet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNoRaw text, if you already have it.
fileUrlNoPublic URL to a PDF or image.
fileBase64NoBase64-encoded file bytes (with fileMimeType).
fileMimeTypeNoMIME type for fileBase64, e.g. application/pdf.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.5

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already indicate this is a mutating, non-idempotent operation (readOnlyHint=false, idempotentHint=false). The description adds valuable behavioral context beyond annotations: it discloses that the operation costs credits from the account wallet, which is important for an agent deciding whether to invoke it. It also clarifies the output shape (document boundaries and summary), which is not in the schema.

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 that front-loads the core function and output, then adds the cost warning. It is compact and every clause earns its place, though it could be slightly more structured with a separate sentence for the cost note.

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?

For a tool with no output schema, the description does a good job of explaining what the agent will get back (document identity, start/end, summary). It also discloses the credit cost, which is a key operational constraint. It does not mention input format requirements or limits, but the schema covers input options and the description is otherwise sufficient for a 4-parameter tool with 100% schema coverage.

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 schema already documents all four parameters (text, fileUrl, fileBase64, fileMimeType). The description does not add parameter-level meaning beyond the schema, but it does clarify that the tool accepts a multi-document bundle, which helps an agent understand that the input should contain multiple documents. Baseline 3 is appropriate.

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 states a specific verb ('classified and split') and resource ('multi-document scan bundle'), and names the outputs: document identity, start/end positions, and a summary. It is clear enough to distinguish from siblings like parserail_classify or parserail_summarize, though it does not explicitly name a sibling alternative.

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 for multi-document bundles that need both classification and splitting, which gives some context for when to use it. However, it does not explicitly state when not to use it or name alternatives such as parserail_classify for classification-only or parserail_summarize for summary-only tasks.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.