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devrobotlabs

@devrobotlabs/visionapi-mcp

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by devrobotlabs

Get a queued Vision API task

vision_get_task
Read-only

Retrieve the status and final result of a previously queued image or PDF analysis task using its task ID. Confirms whether a task is still processing or finished, returning transcription data without extra charges.

Instructions

Status, and once finished the result, of a queued task.

Free — no credits consumed. The result was already paid for when the task was submitted.

Call this with the id from a call that was queued — either one you made with mode:"async", or one where polling ran out of time and the answer told you to come back. A task that is still "queued" or "processing" has NOT failed; it is working, and re-submitting the file would be a second charge for the same work.

Results are kept for 7 days. After that only the metadata survives and the file has to be sent again.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNomarkdown (default) — compact, readable, absent fields summarised rather than repeated. compact_json — the same information as data, with _not_found and _low_confidence arrays, for when you will parse it. json — the API response verbatim; use it when you are writing HTTP code against the contract.markdown
task_idYesThe id returned when a call was queued.
max_charsNoCeiling on transcription text in the response. Raise it only if you truly need more than 20 000 characters.

Schema Changelog

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

  1. First observedv1.0.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true and openWorldHint=true, but the description adds important behavior: it is free (no credits consumed), results are kept for 7 days, and after that only metadata survives. It also explains that a queued state is working, not failed. However, it does not specify details like the exact structure of the result or how errors are reported.

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?

The description is concise and well-structured. It leads with a clear purpose sentence, then provides key behavioral details and usage notes in short paragraphs. Every sentence adds value, and the formatting makes it easy to scan.

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

Completeness5/5

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

Given that there is no output schema, the description compensates by explaining what the result contains ('Status, and once finished the result'). It covers usage context, cost, data retention, and the meaning of intermediate states. For a tool with three simple parameters and clear behavior, this is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for parameters, so the baseline is 3. The description adds value by explaining the format parameter with details on each enum value (markdown, compact_json, json) and when to use each. It also provides guidance on max_chars: 'Raise it only if you truly need more than 20 000 characters.' This adds semantic context beyond the schema.

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 the tool's purpose: 'Status, and once finished the result, of a queued task.' It identifies the specific resource (a queued Vision API task) and the action (get status/result). It distinguishes itself from siblings by referencing queued tasks and explaining the context of async calls or polling timeouts.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance: when to call it (with an id from a queued call, either from mode:"async" or when polling ran out of time), and what not to do (re-submitting the file would be a second charge). It also clarifies that queued/processing states are not failures, which helps the agent avoid unnecessary re-submission.

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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