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sourcing

by m2nho
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

cancel_collection

Stop a collection job in progress, leaving previously collected data intact.

Instructions

돌고 있는 수집을 중단한다. 그때까지 수집한 레코드는 그대로 남는다.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "job_id": "<job_id>"
    },
    "name": "cancel_collection"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full disclosure burden. It usefully reveals that previously collected records are preserved, which is the main side-effect concern for a cancel operation. However, it does not state whether cancellation is reversible, what happens to the job status, or what response the caller should expect.

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?

The description is one compact sentence with the main action front-loaded and the key side effect stated immediately after. There is no redundant or filler content.

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 single-parameter cancel tool with no output schema, the description covers the core purpose and the most important behavioral consequence. It could have added guidance on where to find job_id or how to verify the job state afterward, but given the low complexity, this is a minor gap rather than a serious omission.

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 never mentions job_id at all. The parameter name is fairly self-explanatory, but the description does not explain where to obtain the job ID or that it must refer to an actively running collection, so it fails to compensate for the missing schema-level documentation.

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

Purpose4/5

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

The description states a specific action: stopping a running collection ('돌고 있는 수집을 중단한다') and adds the meaningful outcome that already-collected records remain. This clearly distinguishes it from sibling tools like start_collection and check_collection, though it does not explicitly reference them.

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 phrase '돌고 있는' (running) implies the tool should be used on an in-progress collection, but there is no explicit guidance about when not to use it or which sibling tool should be used instead. Usage context is present but only implicitly.

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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