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chacharin

mcp-lightrag

by chacharin

cancel_pipeline

Stop a running indexing pipeline job and mark in-progress documents as failed. Verify current status first to see what gets cancelled, or receive a not-busy response if none is active.

Instructions

Request cancellation of the currently-running indexing pipeline job. Documents already in progress will be marked FAILED. Use get_pipeline_status first to see what would be cancelled; returns status='not_busy' if nothing is running.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral disclosure burden and does so well: it warns that 'Documents already in progress will be marked FAILED' and documents the not_busy return case. It could add a bit more context about idempotency or what happens to queued documents, but the key side effects are disclosed.

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?

Three short sentences, each with a distinct job: state the action, disclose the destructive side effect, and provide pre-call guidance. There is no filler or repetition, and the core purpose is front-loaded.

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

Completeness5/5

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

For a zero-parameter cancellation tool with an output schema present, the description covers the essential context: what gets cancelled, what happens to in-progress documents, what to check beforehand, and what is returned when nothing is running. Nothing needed to invoke the tool correctly is missing.

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

Parameters4/5

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

The tool has zero parameters, so there is no parameter meaning for the description to clarify. The schema is empty and fully covered, and the description correctly focuses on behavior rather than inventing parameter details. Baseline 4 applies for a zero-parameter tool.

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 names a specific action ('Request cancellation') and a specific resource ('currently-running indexing pipeline job'), making it clear what the tool does. It also distinguishes this from the many read-only siblings like get_pipeline_status and get_scan_status by focusing on the cancellation side effect.

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

Usage Guidelines5/5

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

The description explicitly instructs the agent to 'Use get_pipeline_status first to see what would be cancelled', giving clear pre-call guidance. It also explains the not_busy return value, which tells the agent when the tool is unnecessary because nothing is running.

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