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Submit Image Tasks

submit_image_tasks
Idempotent

Queue 1-12 image generation or editing tasks asynchronously, return immediately, and check results later by task ID.

Instructions

批量登记1–12个后台图像任务并立即返回,不等待绘图/下载(会在后台收费)。

每项task_id在checkpointer/thread_id内唯一且稳定,同内容复用;任何冲突全批不新增。 每项可选model/api_format(auto)/endpoint(auto);变体按显式resolution路由。 Flash-lite仅Gemini/Chat;nano-banana-pro仅DALL·E;gemini-nano仅DALL·E Generations/Gemini/Chat。 查询get_image_tasks;queued/preparing/running是正常状态,unknown不能盲目重交。 MCP进程关闭时未发送任务可在重启后继续,已可能发送任务不自动重试。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tasksYes
thread_idYes
checkpointerYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tasksYes
thread_idYes
next_cursorNo
checkpointerYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations it discloses that billing happens in the background, that task_id is unique/stable within checkpointer/thread_id with content reuse, and critically that any conflict aborts the entire batch. It also explains restart semantics (unsent tasks resume, possibly-sent tasks do not auto-retry). This is exactly the extra behavioral context annotations cannot carry.

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?

The most important behavior (immediate return, no waiting) is front-loaded, and each subsequent line carries distinct information. It is dense and telegraphic but nearly every clause earns its place; a little more structure would have made it cleaner.

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

Completeness5/5

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

For a complex nested batch-submission tool with an output schema (so return values need not be described), the definition covers idempotency, conflict behavior, billing, model routing, status interpretation, and restart semantics. Nothing an agent needs to invoke it safely is missing.

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

Parameters4/5

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

Top-level schema coverage is 0%, so the description must compensate, and it largely does: it explains task_id uniqueness/conflict semantics and model/api_format/endpoint defaults, and adds routing rules (Flash-lite only Gemini/Chat, nano-banana-pro only DALL·E, gemini-nano only DALL·E Generations/Gemini/Chat) plus resolution-based variant selection. It does not fully decode every nested field, so not a 5.

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+resource+scope: batch-registers 1–12 background image tasks and returns immediately without waiting for rendering/download. It distinguishes itself from get_image_tasks by explicitly naming it as the query counterpart, so an agent can route correctly without opening either schema.

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?

It gives clear conditional guidance: use get_image_tasks to query, treat queued/preparing/running as normal, and do not blindly resubmit on 'unknown'. It also supplies model-routing constraints. It doesn't explicitly compare against plan_ecommerce_images or cancel_image_tasks, so it stops short of a full when/when-not map.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.