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AIWorkhub

AIWorkhub

by shrec
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

aiworkhub_manager_resource_status

Read-only

Retrieves the current holder, ordered waiters, priorities, and wait times for a hub-managed resource queue, so managers can inspect contention and plan scheduling.

Instructions

MANAGER READ: queue of a hub-managed resource such as cpu_heavy.

Returns the holder, the waiters in the order they will be served, and each entry's priority and wait time, from the runtime database.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "aiworkhub_manager_resource_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
resourceNoHub resource name, e.g. cpu_heavy; empty returns every known resource.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.12.98

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuine behavioral context beyond that: the data comes from the runtime database, and waiters are returned in service order, which is the key semantic an agent needs to reason about the queue. It does not describe pagination or behavior for an idle resource, but that is minor here.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with the scope constraint front-loaded via the 'MANAGER READ' prefix. The enumeration of return fields edges toward restating what the output schema already provides, but it remains tight and readable.

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 one-parameter read tool with annotations and an output schema, this is essentially complete: an agent knows it reads a resource queue from the runtime DB and what shape of answer to expect. The only untouched detail, behavior when the queue is empty, is reasonably covered by the output schema.

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% and the single parameter documents its default and the empty-string behavior (all resources), so the schema carries the load. The description only restates the cpu_heavy example and adds no new meaning about 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 names a specific verb and resource: a read of the queue for a hub-managed resource, naming cpu_heavy as an example. It is clearly distinct from status siblings such as loop_status or recipe_run_status, though it never explicitly contrasts itself with any of them.

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 'MANAGER READ' prefix implies this is a read-only inspection call to be used when checking resource contention, but there is no explicit when-to-use statement, no exclusion, and no named alternative. Usage is implied rather than stated.

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

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