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wait_for_image_project

Poll an image project until it completes, errors, is canceled, or times out. Returns the final project JSON and, when complete, attempts to inline image 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

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does substantial work: it discloses poll termination conditions, the return value (final project JSON), the conditional inline-download attempt for Inspector/compatible clients, and that download fields are sanitized. It stops short of describing what the return looks like on error, cancel, or timeout, and what 'sanitized' means precisely.

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

Conciseness5/5

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

Three sentences with no filler: the first establishes the core loop, the second covers the return value and client compatibility, and the third is a high-value usage warning about URL integrity. Every sentence earns its place and the essential purpose is front-loaded.

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?

For a polling tool with six parameters, no output schema, and no annotations, the description covers the main loop and download behavior but leaves meaningful gaps: parameter semantics are undocumented, failure-mode return values are unspecified, and there is no mention of how this relates to the create_image siblings whose projects it awaits. It is adequate for basic use but incomplete for nuanced calls.

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%, so the description must compensate, but it never defines any of the six parameters. It only indirectly references download-related behavior ('attempts to inline image downloads', 'sanitized download fields') and polling, which gives partial context for include_inline_downloads, max_inline_downloads, max_bytes_per_download, and the timeout/interval parameters. Parameter names and defaults are self-explanatory, but direct documentation is absent.

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 states a specific verb ('Poll'), a specific resource ('an image project'), and the exact terminal conditions (completes, errors, is canceled, or times out). This clearly distinguishes it from sibling wait_for_audio_project and wait_for_video_project, since the resource type is named explicitly.

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

Usage Guidelines3/5

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

Usage is implied rather than explicit: the description says it polls an image project but never states 'use this after creating an image project' or contrasts it with the project-retrieval siblings like image_projects_retrieve_details. An agent can infer the intended context from the name and the create_* siblings, but no explicit when/when-not guidance is given.

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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