video_queue
POST /v1/video/queue — paid settle+enqueue. Prefer generate_video for agents.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| audio | No | ||
| model | Yes | Live video model id from get_models | |
| prompt | Yes | ||
| duration | No | ||
| resolution | No | ||
| aspect_ratio | No |
POST /v1/video/queue — paid settle+enqueue. Prefer generate_video for agents.
| Name | Required | Description | Default |
|---|---|---|---|
| audio | No | ||
| model | Yes | Live video model id from get_models | |
| prompt | Yes | ||
| duration | No | ||
| resolution | No | ||
| aspect_ratio | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true, readOnlyHint=false, and idempotentHint=false, so the bar for added context is lower. The description adds 'paid' (cost implication) and 'enqueue' (queued/async behavior), which are useful. However, it does not clarify what 'settle' actually does, what side effects occur, or what gets destroyed, leaving the most consequential behavior vague.
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 very short and front-loads the endpoint, payment semantics, and the preferred alternative. Every phrase contributes something, though 'settle+enqueue' is compressed to the point of being cryptic. Still, there is no wasted text.
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 paid, non-idempotent, destructive-hinted operation with six parameters and no output schema, this description is under-specified. It does not explain return values, job tracking, polling via wait_for_video/video_retrieve, or how to construct the request. The routing hint is useful, but it cannot compensate for the missing operational details.
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?
Schema description coverage is only 17%, and the description adds no parameter-level meaning. It does not mention model, prompt, duration, resolution, aspect_ratio, or audio, and the only schema description is for model. With six parameters and almost no schema coverage, the description leaves the agent without the information needed to construct a valid call.
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 identifies the action as 'paid settle+enqueue' on the video queue, which conveys a specific operation, and explicitly distinguishes it from generate_video by saying 'Prefer generate_video for agents.' The phrase 'settle+enqueue' is somewhat jargon-heavy, but the resource and verb are clear enough to separate it from siblings.
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?
The description gives direct routing guidance: 'Prefer generate_video for agents' names the alternative and the condition under which it should be chosen. It does not fully explain when video_queue itself should be used, but the paid/queue framing implies a non-agent, payment-settling workflow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several video tools are effectively duplicates: generate_video and video_queue both target POST /v1/video/queue, while get_generation_status and video_retrieve both call POST /v1/video/retrieve. The non-video tools are distinct, but these overlapping boundaries make it hard for an agent to choose the correct variant.
Tool names are uniformly snake_case and many follow a verb_noun pattern such as create_key, list_keys, and get_models. However, the video tools use an object-first video_* pattern, and names like agent_me, chat_completions, and funding_instructions break the dominant convention.
At 18 tools, the surface is on the heavy side, and the count is inflated by lower-level variants that duplicate agent-facing tools such as video_queue vs generate_video and video_retrieve vs get_generation_status. A leaner set could consolidate these while still covering account, key, model, image, and video workflows.
The set covers the account/key lifecycle, funding and price controls, model discovery, chat, image generation, and a full video quote/queue/status/retrieve/cleanup flow. It also provides request-trace recovery and capacity checks, so agents have no obvious dead ends for the stated domain.