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Unity MCP Server

Unity MCP Server

by rachitkumarrastogi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

list_ai_prompt_or_config_assets

Scan Unity Assets for JSON and Markdown files that appear to be AI prompts, RAG data, or LLM configurations, helping locate relevant assets without opening the Unity Editor.

Instructions

Heuristic scan for JSON/MD assets that look like prompts, RAG, or LLM config under Assets.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_ai_prompt_or_config_assets"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.2

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral load. It does disclose the key trait that results are a 'heuristic scan' — implying possible false positives and a content-based rather than path-based match — which is genuinely useful beyond structured data. However it is silent on read-only safety, cost of scanning, and what the matches 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler; every phrase adds scope information. It is arguably a touch terse, since a clause on result shape would cost little.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-param listing tool this covers purpose and scope, but with no output schema the description should say what a 'match' returns (asset paths, scores, file snippets) and how strict the heuristic is. Those gaps matter for an agent deciding whether to trust the list.

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?

Zero parameters, so the baseline is 4. The description correctly implies no filtering inputs are accepted, and there is nothing further to explain.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb (heuristic scan) plus a concrete resource (JSON/MD assets under Assets that look like prompts, RAG, or LLM config). The scope is narrow enough to separate it from broad siblings such as list_assets_by_extension or list_ml_model_assets, though it never names an alternative explicitly.

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?

No when-to-use or when-not guidance is given. Adjacent siblings like list_ai_skills and find_ai_related_scripts exist, but the description offers no signal about choosing between them, leaving the agent to infer usage from the name alone.

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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