Permanently delete the rendered video. This action is not reversible, please be sure before deleting.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Unique ID of the video project. This value is returned by all of the POST APIs that create a video. |
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 full responsibility for behavioral disclosure. It clearly states that deletion is permanent and irreversible, which is the critical behavioral trait for a destructive operation. It does not cover authorization or response behavior, but the core consequence is disclosed.
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?
Two short sentences with no filler: the action is stated up front and the irreversible warning follows immediately. Every word earns its place.
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 one-parameter destructive operation with no output schema, the description provides the essential context: what is deleted and that it is permanent. It omits error/not-found behavior, but the definition is sufficient for an agent to invoke the tool correctly.
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 schema already documents the single 'id' parameter completely, including an example and how it is returned. The description adds no parameter-specific meaning, so it meets the schema-covered baseline of 3 but does not exceed it.
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 uses a specific verb 'delete' and names the target resource ('rendered video'), so an agent knows this is the destructive counterpart to video_projects_retrieve_details. It does not explicitly differentiate from audio_projects_delete or image_projects_delete, but the resource phrase plus the tool name make the scope clear.
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?
There is no guidance on when this tool should be chosen over alternatives, and no mention of prerequisite steps such as retrieving the project first. The 'please be sure' caveat is a caution, not a when-to-use or when-not-to-use guide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Most generation tools target distinct media types or effects (e.g., clothes changer, head swap, lip sync), but several boundaries blur: ai_image_editor_create_image is a generic edit tool that overlaps conceptually with ai_face_editor_edit_image, ai_image_upscaler_create_image, and background remover. The wait_for_*_project helpers also overlap functionally with the *_projects_retrieve_details status tools, and ai_voice_cloner_create_audio vs. ai_voice_generator_create_audio are easy to confuse by name.
Naming conventions are mixed: many tools follow ai_<product>_create_<media>, but others are product-first (animation_create_video, body_swap_create_image) and resource-group tools follow a different noun_verb pattern (audio_projects_retrieve_details, video_projects_delete). Verbs are inconsistent too (create_image, edit_image, detect_faces, retrieve_details, wait_for, fetch), so an agent cannot reliably predict the next tool name.
At 44 tools, the set is heavy: it includes 27 generation tools plus three wait helpers, three status retrieval tools, three delete tools, three fetch helpers, and upload/ping utilities. While the underlying product is broad, many helpers could be consolidated, and the overall surface exceeds the range where each tool earns a clear place.
The lifecycle is mostly covered for image, video, and audio projects: create, poll/retrieve, fetch download, delete, and file upload/presigned-URL generation are all present. However, there is no project listing or cancel operation, and face detection only has detect/details with no delete or wait helper, leaving some workflow gaps an agent must work around.