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wait_for_audio_project

Poll an audio project until it completes, errors, is canceled, or times out. Returns the final project JSON and, when complete, attempts to inline audio downloads for Inspector or compatible clients. Returns sanitized download fields. Use exact_download_urls[n] or downloads[n].url exactly as returned; do not shorten it, remove query parameters, or append expiration metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
timeout_secondsNo
max_inline_downloadsNo
poll_interval_secondsNo
max_bytes_per_downloadNo
include_inline_downloadsNo

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden. It discloses polling until terminal states, final project JSON return, attempted inline audio downloads, sanitized download fields, and the requirement to use returned URLs exactly. It could add more detail on timeout/error shape or authentication, but core behavior is well disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences with the purpose front-loaded, followed by return behavior and a crucial URL-handling caveat. The content is dense but each sentence earns its place; no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers terminal states, final response content, and URL usage instructions. However, with six parameters, no output schema, and no annotations, it leaves parameter behavior and timeout/error outcomes underspecified. It is adequate for a simple poll tool but not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not compensate. It explains response fields like exact_download_urls and downloads[].url, but gives no semantics for timeout_seconds, poll_interval_seconds, max_inline_downloads, max_bytes_per_download, or include_inline_downloads. The parameter names and defaults are suggestive, but meaningful behavioral meaning is missing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool polls an audio project until it reaches a terminal state, names the resource ('audio project'), and specifies the outcome ('final project JSON' and inline downloads). This distinguishes it from sibling wait_for_image_project and wait_for_video_project tools, and from audio_projects_retrieve_details which is a single retrieval.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description makes the intended use clear: wait on an audio project for completion, error, cancellation, or timeout, then receive the final result. It does not explicitly contrast with alternatives like audio_projects_retrieve_details or fetch_audio_download, nor state when not to use this tool, but the polling context is evident.

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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TDQS

A3.9/5.0
Disambiguation3/5

Most tools are differentiated by product-specific prefixes (e.g., lip_sync, text_to_video, image_upscaler), but the set contains many overlapping create_image/create_video tools, and generic editors like ai_image_editor_create_image and ai_video_editor_create_video blur boundaries with their more specific counterparts. Face/body swapping tools also occupy a similar conceptual space, requiring careful description reading to avoid misselection.

Naming Consistency4/5

Names generally follow a descriptive snake_case pattern of feature plus action (e.g., text_to_video_create_video, image_projects_delete, wait_for_image_project). Minor inconsistencies like ai_face_editor_edit_image versus the dominant create_image suffix, and the mixed ai_ prefix usage across tools, prevent a perfect score.

Tool Count2/5

44 tools is a large surface for an MCP server, even for a broad media-generation API. The count exceeds the 25+ threshold and creates a heavy selection burden, especially with over a dozen create tools for images and videos.

Completeness4/5

The surface covers the full create-to-download workflow for image, video, and audio: creation, status polling, wait helpers, fetch helpers, delete, and asset upload support. Minor gaps include no list/cancel endpoints and no general project search, but agents can complete core tasks without dead ends.

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