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runtime-query

Query runtime game state in Play Mode: find MonoBehaviours by type name and read their public fields and properties to verify game logic, check object states, and debug component values.

Instructions

Query runtime game state in Play Mode. Find MonoBehaviours by type name and read their public fields and properties. Useful for verifying game logic, checking object states, reading scores, debugging component values, etc. Works with any MonoBehaviour in the scene — no project-specific setup required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNameYesFull or partial type name of the MonoBehaviour to find (e.g. 'PlayerController', 'GameManager', 'MyNamespace.EnemyAI').
fieldsNoSpecific field or property names to read (comma-separated). If empty, reads all public instance fields and properties.
findAllNoIf true, find all instances. If false, find first instance only.false
maxResultsNoMaximum number of instances to return when findAll=true (default: 10).10
Behavior3/5

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

No annotations exist, so the description must fully disclose behavior. It implies read-only operation ('Query', 'read') and states no setup required, but does not explicitly guarantee no side effects or mention performance impacts. Adequate but could be more explicit.

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 two sentences with no waste. First sentence states core purpose, second adds use cases and a feature. Front-loaded and efficient.

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 tool with 4 parameters and no output schema or annotations, the description covers what the tool does, how it works, and use cases. It could mention the return format or limitations (e.g., only public members), but is largely complete.

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?

Input schema has 100% description coverage, so baseline is 3. The description adds marginal value by explaining the overall purpose of reading fields, which helps understand parameters, but does not significantly enhance parameter meaning beyond the schema.

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 action ('Query', 'Find', 'read') and resource ('runtime game state', 'MonoBehaviours') with specific verb+resource. It distinguishes from siblings like 'runtime-invoke' (which likely invokes methods) by focusing on reading state.

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

Usage Guidelines4/5

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

It provides concrete use cases ('verifying game logic, checking object states, reading scores, debugging') but does not explicitly mention when to avoid using it or compare to alternative sibling tools for writing or calling methods.

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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