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RiasJ1Dar

glm-orchestrator

by RiasJ1Dar

Скасувати запуск

glm_cancel

Cancel an ongoing model run by providing its run ID to stop execution and free resources.

Instructions

Обриває запуск, що виконується.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
run_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of disclosing side effects. It only says the run is aborted; it does not reveal whether cancellation is irreversible, what happens to results already produced, or whether it errors on non-running runs. This is a meaningful gap for a destructive-ish operation.

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 a single short active sentence with no filler. The core verb and target are front-loaded, making it easy to parse quickly. All the conciseness concerns are separate from the lack of detail, which is captured in other dimensions.

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?

For a simple one-parameter cancel tool, the basic call shape is inferable and the 'running' qualifier is a useful precondition. However, with no annotations and no output schema, the description should ideally mention what happens after cancellation, whether it is idempotent, and whether it only applies to running runs. The gap is moderate but not severe.

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?

The input schema only provides a required string run_id, and schema description coverage is 0%. The tool description does not explain what run_id refers to, how to obtain it, or any format expectations. The parameter name is self-descriptive, but the description itself adds no parameter-level meaning.

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 ('обриває' / aborts) applied to a specific resource ('запуск' / run), and qualifies it as a running run. This clearly identifies the tool as the cancel counterpart to glm_run or glm_wait, though it does not explicitly name those siblings.

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 qualifier 'що виконується' implies the tool should be used on in-progress runs, which is a useful usage clue. However, there is no explicit guidance about when not to use it, what alternatives exist (e.g., glm_wait or glm_status), or what preconditions apply.

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