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docuprox
by docuprox

process_job

Submit an image, PDF, or ZIP for asynchronous DocuProx processing, returning a job ID for status tracking.

Instructions

Submit a document (image, PDF, or zip) for asynchronous processing via DocuProx. Reads the file from disk and uploads it as multipart/form-data. Returns a job_id you can track with job_status or poll_job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesAbsolute or relative path to the document on disk (jpg, png, pdf, zip).
prompt_jsonNoCustom extraction schema (JSON object or string).
template_idNoUUID of the DocuProx template. Omit to use agentic mode.
document_typeNoDocument category (required in agentic mode).
static_valuesNoKey-value pairs overriding STATIC template placeholders.
custom_instructionsNoFree-text instructions for the AI.

Schema Changelog

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

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior4/5

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

No annotations exist, so the description carries the full behavioral burden. It discloses that the tool reads from disk, uploads as multipart/form-data, is asynchronous, and returns a job_id, which are the key runtime behaviors. It could also mention failure conditions or file-size limits, but the core behavioral profile is transparent.

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?

Three sentences with no filler: purpose, transport mechanism, and return/tracking behavior. The most important information is front-loaded and every sentence earns its place.

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 an async upload/processing tool with no output schema, the description covers the input, the asynchronous behavior, and the returned handle, while pointing to the correct tracking tools. It does not describe how parameters interact or when process_agent should be used instead, but the rich 100% schema coverage compensates for most missing parameter context.

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 input schema already documents all six parameters clearly (e.g., dicurrent_type required in agentic mode, tedplate_id UUID). The tool descriptions adds little parameter-level meaning beyond the note that file_path refers to a file on disk, so 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 opens with a specific verb and resource — 'Submit a document ... for asynchronous processing via DocuProx' — so the agent knows what action is being performed. It also names the supported input types and points to job tracking tools, but it does not explicitly differentiate from the sibling process_agent, leaving some ambiguity among submission entry points.

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

Usage Guidelines4/5

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

It provides clear context: use this tool to upload a file from disk and start asynchronous processing, then track it with job_status or poll_job. There are no explicit exclusions or 'when not to use' conditions, and no guidance on when process_agent would be the better choice, but the intended scenario is otherwise clear.

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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