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cancel_note

Cancel a running or queued video-to-notes task, stopping further processing at the next checkpoint. Useful when you need to abort an ongoing note generation before completion.

Instructions

取消一个进行中/排队的笔记生成任务(协作式:在下一阶段边界生效,LLM 总结时每 chunk 检查)。

返回 {ok, task_id, status, message?}。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure. It reveals that cancellation is cooperative and non-immediate, checking at each chunk during LLM summarization. It also provides the return structure. It does not mention side effects on partial outputs or idempotency, but the core behavior is transparent.

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?

Two sentences: the first states purpose and key behavioral nuance, the second lists the response shape. No redundant words, front-loaded and efficient.

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

Completeness4/5

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

For a simple cancellation tool with one parameter and an output schema described, the description covers purpose, behavior, and response. It lacks details on error cases or whether partial results are cleaned, but these are not critical for basic usage. Overall, it is sufficiently complete.

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

Parameters3/5

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

The schema has only task_id with no description coverage. The description implies that task_id identifies the note generation task and includes it in the return, but does not add explicit details on how to obtain it or its format. Baseline 3 is appropriate given a single parameter and clear context from the tool name.

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?

Description explicitly states 'cancel an ongoing/queued note generation task' with a specific verb and resource. This clearly distinguishes it from sibling tools like get_task_status (status check) and cleanup_note (file cleanup).

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?

The description gives the context that cancellation is for ongoing/queued tasks and notes the cooperative timing ('takes effect at the next stage boundary'). However, it does not explicitly mention when not to use it or suggest alternatives (e.g., cleanup_note for already-completed tasks), leaving usage guidance implicit.

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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