get_job_status
Poll an async transcript job and get a download URL when ready.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | Transcript job ID. |
Poll an async transcript job and get a download URL when ready.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | Transcript job ID. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It usefully discloses that the job is async and that a download URL appears only when the job is ready, but says nothing about terminal failure/cancelled states (relevant given cancel_job exists), polling cadence, or whether the call blocks.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no filler; the operation and its payoff are conveyed in under a dozen words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description is the only source of return information, and it covers only the success case (download URL when ready). It omits the non-ready response shape, failure states, and what an agent should do while waiting, leaving a real gap for a polling tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
One parameter with 100% schema description coverage, so the schema already defines job_id as the transcript job ID. The description adds no format, source, or lookup guidance beyond the name itself, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Names a specific verb (poll) and resource (async transcript job) and states the outcome (download URL when ready). It does not explicitly distinguish itself from siblings like get_download_url or get_transcript, which an agent could conflate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
"Poll" implies a repeated-call usage pattern and "when ready" hints at a state-dependent result, but the description names no alternatives (e.g., get_download_url, get_transcript) or conditions for choosing them. Usage is inferable rather than stated.
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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