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aya_games_detectar_engine

Detect the game engine or framework behind a project by examining real workspace evidence, covering Godot, Unity, Unreal, Phaser, Three.js, Flame, libGDX, GameMaker, Defold, RenPy, and LÖVE.

Instructions

Detecta projeto/engine de game por evidencias reais do workspace: Godot, Unity, Unreal, Phaser, Three.js, Flame, libGDX, GameMaker, Defold, RenPy ou LÖVE.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does add one meaningful trait: detection is 'por evidencias reais do workspace', indicating real file inspection rather than declared config. However, it omits whether the operation is read-only, what happens when no engine is detected, and what the return payload looks like (single engine vs. ranked list, confidence, version).

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?

A single sentence with the verb and resource front-loaded, followed by a comma-separated engine enumeration. Every element earns its place; the engine list is high-value routing information and there is zero 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 zero-parameter tool with no annotations and no output schema, the description covers the essential selection criteria: what it detects, the detection basis, and the full supported engine set. The main gap is the missing return contract — no output schema exists to explain the result shape, and the description never mentions no-match behavior or whether results include confidence/versions.

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?

The tool takes zero parameters (empty input schema, 0 required), so there is nothing for the description to document. Per the 0-parameter baseline, this is a 4; the description correctly focuses on behavior rather than nonexistent parameters.

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 states a specific verb and resource: 'Detecta projeto/engine de game por evidencias reais do workspace'. It enumerates the exact supported engines (Godot, Unity, Unreal, Phaser, Three.js, Flame, libGDX, GameMaker, Defold, RenPy, LÖVE), which distinguishes it from sibling tools like aya_games_validar (validation), aya_games_checklist, and other 'detectar' tools (aya_framework_detectar_rota, aya_dominio_detectar).

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 engine list implies when the tool applies (workspace shows evidence of any listed engine), but the description never states explicit when/when-not conditions and does not name alternatives to exclude, such as aya_games_validar or aya_games_assets_inventariar. Usage context is inferable from the name and engine list, not explicitly stated.

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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