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matt-coppinger

Horizon MCP Server

diagnose_session

Diagnose a user session by retrieving logon timing, display metrics, historical performance, processes, and remote apps in one call. Get partial results even if some aspects fail.

Instructions

Retrieve diagnostic information for a user session in a single call.

Fetches any combination of: logon timing breakdown, real-time display protocol metrics, 15-minute historical performance, running processes, and active remote applications. Results are keyed by aspect name; a failed aspect returns its error message as a string rather than failing the whole call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aspectsNoDiagnostic data to retrieve: logon_timing, display_performance, historical_performance, processes, remote_applications. Defaults to all aspects.
session_idYesSession ID to diagnose

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

No annotations are present, so the description must carry behavioral disclosure. It does this well by explaining result keying by aspect name and the partial-failure contract: a failed aspect returns its error message as a string rather than failing the whole call. It could add permission or response-size context, but the core behavior is clear.

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 tight sentences with the main purpose front-loaded and the aspect list and error behavior in the second sentence. No filler or redundant restatement of the schema.

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 2-parameter diagnostic tool with an output schema, the description covers what the call returns and how failures behave. It is complete enough to select and invoke the tool correctly. It could be improved by pointing to alternatives, but that gap is already captured in usage_guidelines.

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 baseline is 3. The prose adds 'any combination' and single-call semantics but mostly restates the aspect enum in different words. It does not add formats or relationships beyond what the schema already provides.

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?

Description opens with a specific verb+resource: 'Retrieve diagnostic information for a user session' and enumerates the five diagnosable aspects. This makes it clear it is a session-diagnostics tool rather than a generic session getter. It does not explicitly name sibling tools like get_session or get_metrics, so some differentiation is left to inference.

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 phrase 'in a single call' and the list of combinable aspects imply the tool is for collecting multiple diagnostics at once. No explicit when-to-use, when-not-to-use, or alternative tool names are given. This is adequate but not strong guidance.

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