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check_job

Read-onlyIdempotent

Check the status/result of a job previously returned by generate_image, generate_video, generate_video_from_image, or generate_video_with_reference.

Besides status/result it reports PROGRESS, so you can tell the person something
truthful instead of "still waiting":
  queue_position — how many jobs are ahead (1 = next to be picked up); only while queued
  queue_seconds  — how long it sat in the queue
  run_seconds    — how long the generation itself has been running
  account_used   — which Google account it ran on, once finished
  while running, also:
    elapsed_s      — seconds since the worker picked it up
    attempt / accounts_total — which of the owner's Google accounts is being tried
                     (attempt > 1 means earlier accounts failed and it rotated on)
    phase          — submitting | voice_synth | polling (polling = Google accepted it and
                     it is rendering; that is the normal wait)
    last_error     — why the previous account's attempt failed (emails masked)
  hint           — the same thing in one human sentence
A job that is queued behind others needs patience; one that has been running far longer
than its model's typical time (see list_models) is the one worth reporting as stuck.
Rotation has a ceiling: a video stops trying new accounts after ~10 min (images and voice
after ~3 min), and stops early when the same error repeats on 3 accounts in a row — the
job then fails with that error and the number of accounts tried, so tell the person the
reason instead of retrying the identical request.

Once status is 'done', SAVE THE FILES: the response carries `download_urls` (no auth
header needed) and `save_as` (filenames). Write them into the user's project — e.g.
./media/<save_as> — and tell them where. The URLs expire within the hour, and the
server's own copy can be reclaimed when its disk fills; the copy in their project is
the one that lasts.

Input Schema

NameRequiredDescriptionDefault
job_idYes
include_previewNo

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?

Annotations only say read-only/idempotent; the description goes far beyond by disclosing the progress fields returned (queue_position, phase, attempt/accounts_total, last_error), the rotation ceiling (~10 min video, ~3 min image/voice, early stop after 3 identical errors), and URL expiry within the hour plus server-side reclamation on disk pressure. That is exactly the mutability/lifetime context annotations cannot express.

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 one-line purpose is front-loaded, then structured bullet lists for progress fields and completion handling; near every sentence carries operational value. It runs long and the rotation paragraph is dense, but the length is justified by information density rather than filler.

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

Completeness4/5

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

With no output schema, the description does the work of describing the return shape (status, progress keys, hint, download_urls, save_as) and what to do with it. The main remaining hole is include_preview and the precise shape/values of the status field (e.g. what values besides 'done' exist).

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

Parameters2/5

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

Schema coverage is 0%, so the description carries the full burden, and it only indirectly explains job_id by naming which generators produce one. The second parameter, include_preview (boolean, default true), is never mentioned at all, so an agent has no basis to decide whether to set it.

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 (check status/result) and resource (job), and enumerates the exact producer tools whose job ids it accepts. An agent can immediately tell this is the follow-up/polling endpoint for the async generators rather than a fresh generation call.

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?

Tells the agent when to call it (after any of the four generate_* tools return a job), how to interpret a long wait (queued = patience; far beyond list_models' typical time = report stuck), and what not to do (do not retry an identical request after rotation ceiling failures). It also gives a post-completion action: save the files instead of stopping at the status read.

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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