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rechnungsapi-mcp

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by Rechnungsapi

Check async PDF analysis status

analyze_pdf_invoice_async_status

Poll the status of a submitted asynchronous PDF invoice analysis job by its job ID. Get updates on processing progress and results.

Instructions

Poll the status of an asynchronous PDF invoice analysis job submitted via analyze_pdf_invoice_async_submit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYesThe job_id returned by analyze_pdf_invoice_async_submit

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that the operation is a status poll tied to a prior submission, but says nothing about polling cadence, terminal status values, behavior for an unknown/expired jobId, or retention of results — all material for a polling tool with zero annotation coverage.

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?

One sentence, no filler, and the operative verb is front-loaded with the origin of the jobId as a trailing clause. Nothing could be trimmed without losing routing information.

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?

There is no output schema and no annotations, so the description must explain the return contract — but it never mentions what statuses come back (e.g. pending/running/succeeded/failed) or what the caller should expect next. For a polling tool whose entire value is the returned status, this is a significant incompleteness.

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% and the single jobId parameter is already documented as 'the job_id returned by analyze_pdf_invoice_async_submit.' The description adds no format, validation, or lifecycle detail beyond the schema, so the baseline 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?

States a specific verb+resource ('Poll the status of an asynchronous PDF invoice analysis job') and ties the resource to the exact sibling that creates it (analyze_pdf_invoice_async_submit). An agent can distinguish this polling tool from the submit tool and from the synchronous analyze_pdf_invoice without opening any schema.

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 usage context by referencing the submit tool, so an agent can infer 'call this after submitting a job.' However it gives no explicit guidance on when to call, how often to poll, or what to do when the job reaches a terminal state.

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