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imjszhang

Open Science MCP

by imjszhang

cancel_run

DestructiveIdempotent

Cancel an active research run to stop processing, then check its status to confirm it has fully stopped.

Instructions

Request cancellation of a specific run. Inspect the returned status, and wait again if cancellation is still draining.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
run_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

The description discloses useful behavioral traits beyond annotations: that cancellation is asynchronous ('request cancellation') and that it may still be 'draining' requiring subsequent waiting. However, it does not fully explain the consequences of cancellation (e.g., whether it is reversible, what resources are affected), and it does not contradict the annotations (destructiveHint=true aligns with the cancellation's potential to terminate resources).

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 composed of two concise sentences that front-load the purpose and then provide actionable guidance on next steps. Every sentence contributes to the agent's understanding of both the action and the follow-up needed. No waste or redundancy.

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?

The description adequately covers the main action and the asynchronous nature, but it lacks details about the returned status format (no output schema) and does not tell the agent what conditions warrant cancellation or how to handle errors. For a tool with destructive implications and no output schema, more context (e.g., typical status values, failure handling) would be beneficial.

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 input schema has one parameter, 'run_id', with no description in the schema (0% coverage). The description references the run but does not elaborate on the format of 'run_id' or how to obtain it (e.g., from 'get_run' or 'start_run'). Since the description does not add significant semantic detail beyond the schema, a baseline of 3 is appropriate, given the simplicity of the parameter.

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 verb ('cancel') and a resource ('a specific run'), which clearly distinguishes it from sibling tools like 'get_run' or 'wait_run'. It also indicates a non-blocking behavior ('request cancellation'), though it could more explicitly contrast with synchronous cancellation or mention that it is for ongoing runs.

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

Usage Guidelines2/5

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

The description gives a hint of the workflow ('Inspect the returned status, and wait again if cancellation is still draining') but does not state when to use this tool versus alternatives like 'wait_run' or 'get_run'. It lacks explicit exclusions (e.g., not for completed runs) and does not mention when cancellation is appropriate or prerequisites (e.g., run must be running).

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