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export_data_table_as_csv

Destructive

Export a Unreal Engine DataTable to CSV as a read-only backup, returning row structure, row count, and the CSV string, with optional UTF-8 file write.

Instructions

Export a whole DataTable to CSV with the native exporter (read-only), returning row_struct, row_count and the csv string, optionally also written to a UTF-8 file. Use it as the backup before import_data_table_csv; nested structs and TMaps do not survive CSV cleanly, so export_data_table_as_json is the faithful copy.

Returns: { table_path, row_struct, row_count, csv, written_to? }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathNoOptional OS path to also write the CSV string to (echoed back as written_to)
data_tableNoAlias of table_path: pass one of the two.
table_pathNoFull asset path of the DataTable.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.2.0
    • addedInput schema / properties / data_table / description
      Added value: +"Alias of table_path: pass one of the two."
    • changedInput schema / properties / table_path / description
      Previous value: -"Full asset path of the DataTable (data_table also accepted)"New value: +"Full asset path of the DataTable."
    • removedInput schema / required
      Removed value: -[
      -  "table_path"
      -]
  2. First observedv1.1.0

TDQS

A3.7/5.0
Behavior1/5

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

The description labels the operation '(read-only)', but the annotations declare readOnlyHint=false and destructiveHint=true. A parenthetical claiming read-only directly contradicts the structured safety profile an agent will trust. Although the description does disclose the optional file write, the read-only label conflicts with the annotations, flagging an Annotation Contradiction.

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?

Front-loads purpose and return shape in two tight sentences, with the alternative-routing note following. Every sentence carries information, though the trailing 'Returns: {...}' is slightly redundant given the prose already lists the fields.

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?

With no output schema, the description compensates by enumerating the return shape (row_struct, row_count, csv, written_to). Guidance to prefer JSON for nested data is present. The only shortfall is the unresolved read-only/destructive tension, which reduces confidence in the side-effect profile.

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 already documents file_path, data_table, and table_path. The description reinforces the optional file write to a UTF-8 file but adds no syntax or format detail beyond the schema. Baseline 3 is appropriate when the schema carries the parameter documentation.

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?

States a specific verb + resource (export a whole DataTable to CSV) and names the exact counterpart tools, import_data_table_csv and export_data_table_as_json. An agent can distinguish what this does versus its siblings without opening any schema.

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

Usage Guidelines5/5

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

Provides explicit when-to-use ('use it as the backup before import_data_table_csv') and when-to-prefer-an-alternative ('nested structs and TMaps do not survive CSV cleanly, so export_data_table_as_json is the faithful copy'). Alternative and selecting condition are both named.

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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