Fill missing storyboard fields for all episodes, improving completeness before image generation. Leaves existing fields unchanged by default; set overwrite to replace them.
(推荐)AI 一键给全集分镜补全空缺字段,默认只填空缺、不覆盖已有(overwrite=true 才覆盖)。提升分镜完整性,出图前做。后台异步,文本步后付。
| Name | Required | Description | Default |
|---|---|---|---|
| overwrite | No | true=覆盖已有字段(默认 false 只填空缺) | |
| episode_id | Yes |
Changes observed during successful MCP inspections.
v0.1.57Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It discloses the critical non-destructive default (no overwrite unless overwrite=true), asynchronous execution, and the billing timing. It doesn't mention how to retrieve status or result, but the described behaviors are the most important ones for safe invocation.
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?
A single compact sentence conveys the key facts: what the tool does, the destructive default, the recommended timing, async behavior, and payment point. Every clause adds useful information, and the most critical safety detail (no overwrite by default) is front-loaded.
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 two-parameter async tool with no output schema or annotations, the description is largely complete: episode scope, overwrite semantics, timing, and async behavior are all covered. It doesn't mention polling via get_autofill_status or what the immediate response contains, but the existence of that sibling and the async note make the invocation safe enough.
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 50%; overwrite is already documented in the schema, and the description reinforces its default behavior. episode_id has no schema description, but the phrase '全集分镜' clarifies that the tool operates on an entire episode's storyboards, which helps an agent infer episode_id's role. This adds some value but doesn't fully compensate for the bare parameter schema.
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 states a specific action: AI one-click completion of missing storyboard fields for an entire episode. It clearly distinguishes this from generation by emphasizing it only fills gaps rather than creating storyboards. The recommended tag and scope (全集分镜) make its purpose immediately recognizable relative to siblings like generate_storyboards.
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?
The description gives clear context: do it before image generation to improve storyboard completeness. It also notes the async nature and payment timing. It doesn't explicitly name alternatives or state when not to use it, but the corrective 'fill gaps, don't overwrite' instruction implies the main use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.