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Private AI Media Generation

Poll a generation job

get_job
Idempotent

Check a running job returned by generate_image — free. Returns {status:'done',url} | running | failed.

Input Schema

NameRequiredDescriptionDefault
jobIdYesjobId returned by the generate endpoint

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / jobId / description
      Previous value: -"jobId returned by /v1/agent/generate"New value: +"jobId returned by the generate endpoint"
  2. Added

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare idempotentHint=true, destructiveHint=false, and readOnlyHint=false, and the description adds genuinely useful context beyond them: the call is free and the terminal states are done/running/failed. It does not address the non-read-only flag (any side effects of polling) or whether job results expire, so it adds moderate value without resolving the gap the annotations leave open.

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?

Roughly fifteen words, front-loaded with the action and the return contract, with no filler sentences. Every clause (source of the job, cost, return states) carries information an agent needs.

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?

For a one-parameter polling tool with no output schema, the description adequately covers the return states and the relationship to generate_image. The remaining gap is operational — no guidance on how or how often to poll, or how long a finished job's URL stays valid.

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 description coverage is 100%, so the single jobId parameter is already documented. The description's phrase 'returned by generate_image' barely sharpens the schema's own 'jobId returned by the generate endpoint', so the baseline 3 applies.

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 and resource ('Check a running job') and ties it directly to its producer ('returned by generate_image'), which cleanly separates it from generate_image and the other generation siblings. The return-shape clause further pins down what the call produces.

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

Usage Guidelines3/5

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

The description implies usage (poll a job you got from generate_image) and notes it is 'free', which helps an agent decide to call it rather than something else. It never states polling cadence, when to stop polling, or what to do on 'failed', so usage is implied rather than explicit.

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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