quiz_video_create_renderQueue a new video render for an existing quiz. Returns the render sessionId; poll quiz_video_get_render until its status is "completed" (typically 1-5 minutes), then call quiz_video_download_render to obtain the signed MP4 URL. The quiz itself is viewable immediately at /quiz/{slug}/ regardless of render status.
| Name | Required | Description | Default |
|---|---|---|---|
| quizId | Yes | ID of the quiz to render into a video. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnly=false), the description discloses the asynchronous nature (polling required, 1-5 minutes), the return of a sessionId, and the immediate availability of the quiz. This added context is valuable and does not contradict annotations, providing a complete picture of expected behavior.
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 three sentences, each earning its place: action, workflow, and an important caveat. It is front-loaded with the core purpose and contains no filler or redundant details.
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?
Given only one parameter and no output schema, the description covers the essential workflow (queue, poll, download) and notes immediate quiz availability. Missing are potential failure modes, but the description is thorough for a simple async rendering tool.
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 coverage is 100%, so the baseline is 3. The description adds minimal extra meaning about quizId beyond the schema (e.g., 'existing quiz'), but it does not elaborate on format or edge cases. The schema already describes the parameter adequately.
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 states the tool's function with a specific verb and resource: 'Queue a new video render for an existing quiz.' It distinguishes itself from sibling tools by naming the subsequent workflow (poll get_render, download_render), making the purpose 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?
Explicit usage guidance is provided: it instructs to poll quiz_video_get_render until status is 'completed' and then call quiz_video_download_render. It also notes that the quiz is viewable immediately, clarifying when this tool is necessary. This effectively guides the agent through the full workflow and alternatives.
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.
Every tool targets a distinct resource and action (create/get/list/update/delete per entity). Overlapping pairs like get_render vs download_render are clearly differentiated by their purpose, and generate_quiz vs create_quiz serve different creation modes. There is no ambiguity between tools.
The vast majority of tools follow a consistent 'quiz_video_<verb>_<noun>' pattern in snake_case. The only deviation is the three discovery tools (get_api_catalog, get_llms_txt, get_openapi_spec) which omit the 'quiz_video_' prefix, though they still use a clear verb_noun structure.
With 30 tools, the server is on the heavier side and exceeds the typical 15-tool guideline. However, the count is justified by the breadth of resources covered (quizzes, questions, hooks, templates, flashcard decks, renders, music, account) and each tool has a distinct role, so the size feels appropriate for a comprehensive API surface.
The server covers full CRUD for most core resources (quizzes, templates, flashcard decks, hooks) and add/list for questions. Minor gaps include no individual question update/delete and no direct render deletion, but these are not critical and the main workflows (create → view → render → download) are fully covered.