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AIWorkhub

AIWorkhub

by shrec
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

aiworkhub_doctor_diagnose

Read-only

Diagnose current failures by running task, dispatcher, source-graph, and manager-route health probes concurrently, then return a verdict with failing probes and the next tool to call.

Instructions

READ-ONLY: what is wrong right now. Runs the task, dispatcher, source-graph and manager-route health probes concurrently and returns one verdict (ok/problem/unavailable) with the non-ok probes and the tool to call next, plus server_process: this answering process's pid, memory and runtime generation. Use first when something fails and the cause is unknown; use aiworkhub_environment_preflight for pre-launch readiness.

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_doctor_diagnose"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.12.68

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/openWorldHint, so the safety profile is covered; the description goes further by disclosing that probes run concurrently, defining the three verdict values, and noting the server_process payload (pid, memory, runtime generation). It does not cover cost/latency or how "unavailable" differs operationally from "problem", which keeps it below a 5.

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?

Leads with the READ-ONLY tag and the core question, then details the probe set and return shape, then closes with routing guidance. Well front-loaded and dense, though the server_process clause is longer than its diagnostic value warrants.

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?

An output schema exists so return values needn't be fully specified, annotations carry the safety profile, and the tool takes no parameters. The description still supplies the verdict vocabulary, the next-tool routing, and the process diagnostics — nothing an agent needs in order to call it 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?

Zero input parameters, so there is nothing for the description to disambiguate and the schema is trivially complete. Baseline 4 applies; the description correctly spends no space on parameter semantics.

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?

States a specific verb and resource: "what is wrong right now" implemented as concurrent task/dispatcher/source-graph/manager-route health probes returning one verdict. Enumerating the four probes distinguishes it from the single-subsystem siblings (aiworkhub_task_health, aiworkhub_dispatcher_health, aiworkhub_source_graph_health) without needing to compare schemas.

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?

Explicit use-first trigger ("when something fails and the cause is unknown") plus an explicit alternative and its condition ("use aiworkhub_environment_preflight for pre-launch readiness"). Both the when and the when-not are named, leaving nothing to inference.

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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