qencode

get_job_status_detailed

Read-onlyIdempotent

Fetch the full, authoritative status of a transcoding job.

Like `get_job_status`, but follows the job's per-job master
`status_url` for the complete detail set: per-rendition output URLs,
sizes, bitrates, durations, and any `warnings`. Use this once a job is
finishing/finished (the jobs card from `list_jobs`, or a snapshot from
`get_job_status`) when you need the concrete output artefacts rather
than just the overall `status`/`percent`.

Flow: the compact `/v1/status` is queried first to learn the
`status_url`; if present and safe, the master endpoint is queried for
the detailed view. The second hop is best-effort: when a job has no
`status_url` yet (e.g. still queued), the URL fails the SSRF host
check, or the master request fails with an API or transport error,
the compact status is returned unchanged instead of raising. Only the
detail set is at risk, not the call — but this is a fallback, not a
guarantee that the tool cannot fail.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`task_token`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`error`	No
`texts`	No
`audios`	No
`images`	No
`status`	No
`videos`	No
`percent`	No
`duration`	No
`warnings`	No
`status_url`	No
`api_version`	No
`source_size`	No
`error_description`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 12, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering safety. The description goes further, disclosing the two-hop request flow, the SSRF host check, and the best-effort fallback that returns compact status on failures. This is valuable behavioral context beyond annotations.

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?

The description is detailed and somewhat long, but every sentence adds value: purpose, usage, flow, and fallback. It is front-loaded with the core purpose and structured logically. The length is justified by the tool's two-hop complexity, though it could be tightened slightly.

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 the complexity (multiple HTTP calls, fallback, SSRF check), the description covers all essential behavior: what is returned, when it falls back, and that only the detail set is at risk. An output schema exists (though not provided), so return values are presumed covered. Nothing critical is missing for an agent to call it correctly.

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?

The schema has one required parameter (task_token) with 0% description coverage. The description implies the token identifies the job via references to list_jobs and get_job_status, but never explicitly explains its purpose or how to obtain it. For a single self-named parameter this is acceptable but not fully compensated.

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 fetches the full, authoritative status of a transcoding job, explicitly contrasting it with the simpler get_job_status. It specifies the resource (job status) and the added value (per-rendition details, warnings), making its distinct purpose unambiguous.

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?

It explicitly tells the agent when to use this tool: once a job is finishing/finished and concrete output artifacts are needed, rather than just overall status. It also implies the alternative (get_job_status) for compact status and describes the fallback behavior, giving clear context for selection.

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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