ai_statusCheck an AI Studio generation's status—queued, running, done, failed, NSFW, or canceled—and get its wait estimate by ID.
Check an AI generation: queued, running, done, failed, nsfw or canceled, with the wait estimate.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower, and the description adds real value by disclosing the result domain (queued/running/done/failed/nsfw/canceled) plus the wait estimate. It does not cover behavior for an unknown id or whether polling is required, but the key behavioral context is present.
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?
One sentence, front-loaded with the action and resource, then the outcome set and the wait estimate. No filler and nothing redundant.
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?
With no output schema, the description usefully enumerates the returnable statuses and the wait estimate. Combined with annotations covering the safety profile, this is close to complete for a one-parameter status check; only id semantics and error behavior are unaddressed.
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?
The single 'id' parameter has 0% schema description coverage, so the description carries the burden. 'Check an AI generation' implicitly identifies the id as a generation id rather than a clip or project id, which is the main ambiguity resolved, but no format or accepted-value guidance is given.
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?
States a specific verb ('Check') and resource ('an AI generation') and enumerates the possible states, so the agent knows exactly what is returned. It is clear on its own but never names how it differs from siblings like ai_list or ai_cancel, which also operate on AI generations.
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?
Usage is only implied: mentioning a 'wait estimate' hints that this is a polling tool to call after ai_generate. There is no explicit statement of when to use it versus ai_list (enumerate generations) or ai_cancel, and no stated prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.