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Universal Game Modder

Universal Game Modder

by doritoman90000
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

read_datatable

Extract all rows and field values from a game DataTable asset, with optional row limit and name filter, for inspecting Unreal or engine data locally.

Instructions

Read a DataTable asset with all rows and field values.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "asset_path": "<asset_path>"
    },
    "name": "read_datatable"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax rows (default 100)
asset_pathYesDataTable asset path
row_filterNoOptional row name filter

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It does disclose the return content (all rows and field values), which is useful given there is no output schema, but it omits pagination behavior, permission requirements, and the interplay with the limit parameter.

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; the resource and scope come first. It is efficient, though very terse, providing no structural cues for the optional filtering parameters.

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 3-parameter tool with no annotations and no output schema, the description covers the core read behavior but does not explain default limits, error cases, or filter semantics. It is minimally adequate rather than 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?

Schema description coverage is 100%, so asset_path, limit, and row_filter are already documented in the schema, establishing a baseline of 3. The description adds no parameter detail beyond what the schema provides, and its 'all rows' phrasing sits in mild tension with the default limit of 100.

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?

The description states a specific verb and resource (read a DataTable asset) and scopes the operation (all rows and field values). However, it does not distinguish this from nearby siblings such as read_asset, read_asset_export, or get_serialized_fields, so an agent must infer which asset-reading tool applies.

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 statement of when to use this tool versus alternatives like read_asset or read_blueprint, and no prerequisites or exclusions are given. The agent gets a purpose but no routing guidance among the many asset/inspection siblings.

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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