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assets-find-built-in

Search Unity Editor's built-in assets like Materials and Shaders from the Resources/unity_builtin_extra folder to locate default resources for your projects.

Instructions

Search the built-in assets of the Unity Editor located in the built-in resources: Resources/unity_builtin_extra. Doesn't support GUIDs since built-in assets do not have them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoThe name of the asset to filter by.
typeNoThe type of the asset to filter by. Schema: "Material" or "Shader" or "Texture2D" etc. (Unity asset type name)
maxResultsNoMaximum number of assets to return. If the number of found assets exceeds this limit, the result will be truncated.10

Implementation Reference

  • The `call_tool` function in `mcp_server.py` handles the execution of MCP tools (including "assets-find-built-in") by writing commands to a filesystem-based IPC mechanism that the Unity Editor monitors.
    def call_tool(name, arguments):
        """Execute a Unity Bridge tool via file IPC. Returns MCP content result."""
        bridge_dir = get_bridge_dir()
        commands_dir = os.path.join(bridge_dir, "commands")
        results_dir = os.path.join(bridge_dir, "results")
    
        # Heartbeat check
        err = check_heartbeat(bridge_dir)
        if err:
            return True, err
    
        # Write command
        command_id = f"{int(time.time())}-{uuid.uuid4().hex[:8]}"
        command = {"id": command_id, "tool": name, "params": arguments or {}}
    
        os.makedirs(commands_dir, exist_ok=True)
        os.makedirs(results_dir, exist_ok=True)
    
        command_file = os.path.join(commands_dir, f"{command_id}.json")
        write_atomic(command_file, json.dumps(command))
    
        # Poll for result
        result_file = os.path.join(results_dir, f"{command_id}.json")
        elapsed = 0.0
    
        while not os.path.exists(result_file):
            time.sleep(IPC_POLL_INTERVAL)
            elapsed += IPC_POLL_INTERVAL
            if elapsed >= IPC_TIMEOUT:
                try:
                    os.remove(command_file)
                except OSError:
                    pass
                return True, f"Timeout after {IPC_TIMEOUT}s waiting for Unity (tool: {name})"
    
        # Read result
        try:
            with open(result_file, "r", encoding="utf-8") as f:
                result = json.load(f)
        finally:
            try:
                os.remove(result_file)
            except OSError:
                pass
    
        is_error = result.get("status") != "success"
        message = result.get("message", "")
        return is_error, message
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 burden. It discloses that built-in assets don't support GUIDs, which is useful behavioral context. However, it doesn't mention other traits like whether this is a read-only operation, performance implications, or error handling, leaving gaps for a search tool.

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 concise sentences with zero waste: the first defines the tool's purpose and scope, and the second adds critical behavioral context about GUIDs. It's front-loaded with essential information and efficiently structured.

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?

Given no annotations and no output schema, the description provides basic purpose and a key constraint (no GUIDs), but lacks details on return format, error cases, or interaction with other tools. For a search tool with 3 parameters, this is minimally adequate but has clear gaps in completeness.

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?

Schema description coverage is 100%, so the schema fully documents the parameters. The description doesn't add any parameter-specific details beyond what's in the schema, such as examples for the 'type' object or search behavior nuances. Baseline 3 is appropriate as the schema handles the semantics.

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 specific action ('Search'), target resource ('built-in assets of the Unity Editor'), and location ('Resources/unity_builtin_extra'). It distinguishes from sibling 'assets-find' by specifying built-in assets and noting they don't have GUIDs, making the purpose unambiguous.

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?

The description provides clear context for when to use this tool: for searching built-in assets that lack GUIDs. It implicitly distinguishes from 'assets-find' (which likely handles regular assets with GUIDs) but doesn't explicitly name alternatives or state when not to use it, missing full explicit guidance.

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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