get_debug_output
Retrieve current debug output and errors from the Godot game engine to identify and resolve issues during development.
Instructions
Get the current debug output and errors
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve current debug output and errors from the Godot game engine to identify and resolve issues during development.
Get the current debug output and errors
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe key behaviors such as whether the output is real-time or cached, if it requires specific permissions, or what format the debug output is returned in. This leaves significant gaps for a tool that likely involves system-level data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that directly states the tool's function with zero wasted words. It's front-loaded and efficiently communicates the essential information, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a tool that likely returns complex debug data. It doesn't explain what 'debug output and errors' entails (e.g., logs, system status, error codes) or how the information is structured, which is crucial for an AI agent to use it effectively in a development or troubleshooting context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the schema description coverage is 100%, so there's no need for parameter details in the description. The description appropriately focuses on the tool's purpose without redundant parameter information, earning a high score for not overcomplicating a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('debug output and errors'), making it immediately understandable. However, it doesn't explicitly differentiate from potential sibling tools like 'get_project_info' or 'get_godot_version', which might also provide diagnostic information, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_project_info' that might overlap in diagnostic contexts, there's no explicit mention of when this tool is appropriate or what distinguishes it, leaving usage unclear.
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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