Skip to main content
Glama

pipeline_cancel_run

Destructive

Cancel an active Microsoft Fabric pipeline run by providing workspace, pipeline, and job instance IDs to halt execution immediately.

Instructions

Cancel a running pipeline execution

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pipelineIdYesThe pipeline ID
workspaceIdYesThe workspace ID
jobInstanceIdYesThe job instance ID to cancel

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.8.0

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true, and the description's 'Cancel' is consistent with that, so there is no contradiction. The description adds no further behavioral context such as irreversibility, idempotency, or effects on downstream steps, but the annotation covers the core destructive nature.

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, front-loaded sentence with no filler words. Every word contributes the core action and target, so it is appropriately concise.

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 three-parameter cancellation tool, the schema fully documents the inputs and annotations establish the destructive behavior. The description states what it does, which is enough for most invocation scenarios, though it omits details like handling of already-completed runs or whether cancellation is asynchronous.

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?

Input schema coverage is 100%, with each parameter described (e.g., 'The job instance ID to cancel'). The description itself adds no parameter-level meaning, so the baseline of 3 applies.

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?

The description clearly states the specific verb 'Cancel' applied to a 'running pipeline execution', which is distinct from pipeline_run, pipeline_get_run_status, and pipeline_delete in the sibling list. The resource and action are unambiguous.

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 intended use is implied: cancel a running pipeline execution. However, the description gives no explicit guidance about alternatives (e.g., pipeline_delete for removing a pipeline definition, pipeline_get_run_status for checking status) or preconditions, leaving some inference required.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mkoziel2000/mcp-fabric-api'

If you have feedback or need assistance with the MCP directory API, please join our Discord server