Skip to main content
Glama
taltal-beep
by taltal-beep

Queue Depths

queue_depths
Read-only

Count waiting messages in each RabbitMQ or Redis queue and identify the workers consuming them to diagnose backed-up or unrouted Celery tasks.

Instructions

Count waiting messages per queue and show which workers consume each one. Works on RabbitMQ and Redis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queuesNoQueue names to check. Defaults to configured queues plus every queue a worker consumes.
timeoutNoSeconds to wait for worker replies. Defaults to CELERY_INSPECT_TIMEOUT.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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?

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that it counts 'waiting' messages and supports RabbitMQ and Redis, but does not disclose authentication needs, rate limits, or other operational behavior.

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?

Two short sentences, front-loaded with the core action and no wasted words.

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?

Given the output schema exists and annotations cover the safety profile, the description is largely complete for a read-only inspection tool. It only misses guidance on how it relates to list_workers, which would help tool selection.

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?

Schema description coverage is 100%, so the schema already fully documents the two optional parameters. The description adds no parameter-level details, which is the baseline when the schema does the heavy lifting.

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?

States a specific verb and resource: 'Count waiting messages per queue and show which workers consume each one.' This clearly distinguishes it from a generic worker listing, but it does not explicitly differentiate itself from the sibling tool list_workers.

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?

No guidance on when to use this tool versus alternatives like list_workers. It only notes technology support ('Works on RabbitMQ and Redis'), which is context rather than usage direction.

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

Deploy Server

Other Tools