get_videoLook up a render started by generate_video. While status is "pending" or "processing" the clip is still being made, so wait about 15 seconds and check again. When it is "completed" the result carries a public URL anyone can open, which you should hand the user directly. When it is "failed" the credits have already been refunded.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The job id returned by `generate_video`. |
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 full burden. It discloses status values, polling delay, public URL on completion, and credit refund on failure—covering key side effects and expected behavior. Thorough and accurate.
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?
The description is tight and front-loaded with the core purpose. Every sentence adds value—status handling, timing, and outcome—without redundancy.
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?
For a single-parameter tool with no output schema, the description fully covers the operational loop: how to interpret statuses, when to poll, what result to return, and what happens on failure. Nothing essential is missing.
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 input schema already documents the parameter fully (job id returned by generate_video). The description adds no extra parameter meaning beyond the schema's coverage, so baseline 3 is appropriate.
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?
The description states a specific verb ('look up'), resource ('a render started by generate_video'), and clarifies its role among siblings. It clearly distinguishes from generation, credit balance, and model listing tools.
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?
Provides explicit polling instructions: wait 15 seconds while pending/processing, check again, and what to do on completed (hand URL) and failed (refunded). This gives clear when-to-use and how to act without needing external hints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.