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export_manage

List export presets, inspect build settings, and execute headless Godot builds via CLI.

Instructions

Project Export Automation, Presets Inspection, and Headless Game Builds.

Ops:

  • list_presets() List all configured platform export targets in export_presets.cfg.

  • get_preset_info(preset_name) Inspect detailed build settings and options for a specific preset.

  • run_export(preset_name, output_path="", debug=false) Execute a headless project export via Godot CLI.

Canonical call shape: {"op": "<verb>", "params": {...}}. Flat op parameters are accepted as a compatibility alias when the client transmits them; op and session_id remain top-level.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opYes
paramsNo
session_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv5.0.28

TDQS

A3.9/5.0
Behavior3/5

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

No annotations exist, so the description carries the burden of disclosing behavior. It does disclose headless CLI execution and a debug flag, which is useful. However, it does not state whether run_export overwrites files, what artifacts it produces, what preconditions exist, or what failure modes look like.

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 bulleted operations are scannable, defaults are inline, and the call-shape note is a single focused paragraph. Every line adds useful information without filler or repetition.

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 three-operation tool with an output schema, the description covers every operation's parameters and invocation format. The main gaps are usage routing relative to siblings and run_export side effects, but the core calling contract is complete enough for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema only exposes op, params, and session_id, with params as a free-form object. The description defines the exact per-operation signatures with defaults, including preset_name, output_path, and debug, and clarifies the canonical call shape plus the flat-parameter compatibility alias. This fully compensates for the 0% schema description coverage.

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 opening line names the domain, and each listed operation uses a specific verb and resource: list_presets lists export targets, get_preset_info inspects preset settings, and run_export executes a headless Godot export. References to export_presets.cfg and the Godot CLI make it clearly distinguishable from broad sibling tools like project_manage.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use or when-not-to-use guidance, and no mention of alternative tools among the dozens of siblings such as project_run, project_manage, or pck_manage. The operations imply their own purpose, but the description does not help an agent choose this tool versus a sibling.

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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