POST /v1/video/quote — no settle, no job. Check clears_now vs price ceiling vs funding before queue.
| 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'no settle, no job', which discloses that this operation does not create or commit to a job, implying a read-only or estimation nature. However, it does not reveal side effects, authentication requirements, rate limits, or response behavior. This is minimal but valuable context, yet insufficient for full transparency.
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 a single sentence and is appropriately short, front-loading the operation and its key distinction. However, the brevity sacrifices essential details, making it terse rather than effectively structured. While every word earns its place, the description is under-specified, so it is concise but not well-balanced.
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?
The tool has 6 parameters, low schema coverage, and no output schema. The description does not explain what the tool returns, how parameters should be used, or how it integrates with sibling tools beyond the 'before queue' hint. It does not even outline the decision logic clearly. An agent would lack the information needed to call this tool correctly, so it is highly incomplete.
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%, meaning the schema provides almost no parameter explanations. The description must compensate but does not mention any parameters, their format, constraints, or usage semantics. It focuses only on the operation's nature, leaving all six parameters (especially the required 'model' and 'prompt') unexplained. This is a critical gap.
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 clearly identifies the tool as a video quote endpoint, with 'POST /v1/video/quote' as the verb and resource. It immediately distinguishes it from related tools by stating 'no settle, no job', which sets it apart from video_queue and video_complete. The operation is positioned as a pre-check ('before queue'), making its purpose specific and unambiguous.
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 provides clear usage context by indicating this should be used 'before queue', implying it is a prerequisite step to video job submission. It also hints at the decision factors (clears_now vs price ceiling vs funding) that should be checked. However, it does not explicitly name alternatives or state conditions under which to avoid this tool, so it lacks explicit exclusions.
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.