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Check a queued conversion

get_conversion_job
Read-only

Check a queued conversion job you submitted.

Returns job_id and status (queued, running, succeeded or failed). A succeeded job includes the markdown when it is under 100 KB, otherwise a result_url to download it (also free). A failed job includes error, one sentence with the reason. Results are deleted 7 days after submission. An expired result is reported in error. Requires an API key.

Credits: free. This tool is not metered.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesThe `job_id` returned by `submit_conversion_job`.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

With annotations only covering readOnly/openWorld, the description carries real behavioral weight: it enumerates all four status values, explains the 100 KB inline-vs-result_url branch, the failure error contract, the 7-day retention and expiry reporting, and the API-key requirement. This is exactly the context an agent needs to interpret responses.

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?

Front-loaded with purpose, then well-organized status/return/retention details. Slightly redundant at the end, where 'Credits: free.' and 'This tool is not metered.' say nearly the same thing, costing some tightness.

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 a single required parameter, existing output schema, and read-only annotations, nothing an agent needs is missing: status semantics, size-based return branch, failure contract, expiry, auth, and cost are all covered.

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 coverage is 100% for the single job_id parameter and its description points back to submit_conversion_job, so the schema already does the work. The prose adds no format or syntax detail beyond that, making 3 the correct baseline.

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 precise verb+resource ('Check a queued conversion job you submitted') and immediately distinguishes itself from submit_conversion_job by scoping to an already-submitted job. An agent can pick this tool over its siblings without ambiguity.

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?

The phrase 'you submitted' and the job_id's provenance ('returned by submit_conversion_job') imply the post-submission polling context clearly. It does not, however, state explicit alternatives or when-not-to-use conditions, e.g. that it should be polled repeatedly until terminal status.

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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