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get_app_output

Retrieve the latest console output from a launched PySide6 app to debug crashes, startup failures, and warnings. Includes print() output, uncaught tracebacks, and Qt/console warnings.

Instructions

Get the last n lines of the launched app's real stdout/stderr: print() output, uncaught tracebacks, and Qt/console warnings.

This is the app's actual console output, captured because launch_app redirects it to a log file. Use this to debug crashes or startup failures. For structured Python logging records use get_logs() instead.

Only works for apps started via launch_app on this server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNo
pidNoApp pid from launch_app. Omit to target the last launched app. Required only when several apps are running and you need a specific one.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  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, the description carries the full behavioral burden. It does well by explaining that the output is actual captured console output, that launch_app redirects stdout/stderr to a log file, and that the tool only works for launch_app-started apps. It stops short of stating empty-app behavior or ordering/availability details, but the output schema likely covers return structure.

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?

The description is concise and front-loaded with the core action. Every sentence earns its place: one defines the output, one explains the capture mechanism, one gives a debugging use case, one routes to the correct alternative, and one states the essential prerequisite.

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 low-complexity tool with two optional parameters and an output schema, the description provides sufficient context: what it returns, why it exists, when to use it, when to use an alternative, and the prerequisite that the app must be launch_app-managed. Nothing critical appears 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?

Schema description coverage is 50%, leaving n undocumented in the schema. The opening sentence compensates by defining n as the number of lines of output to retrieve. The pid parameter is thoroughly described in the schema, including its default behavior and when it is required, so the description does not need to repeat it.

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 clearly states the tool retrieves the last n lines of the launched app's real stdout/stderr, and enumerates what that includes: print output, tracebacks, and warnings. It also explicitly distinguishes itself from the sibling get_logs by contrasting console output with structured logging records.

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 gives concrete when-to-use guidance: debug crashes or startup failures. It explicitly names get_logs() as the alternative for structured Python logging records, and states the important prerequisite that the app must have been started via launch_app on this server.

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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