Skip to main content
Glama
CarlxsMG

UEAgent

by CarlxsMG
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Local

get_data_table_column

Read-onlyIdempotent

Reads one column across every row of a DataTable as ExportText strings, preserving TMaps, soft references, and tags; verifies cell edits and errors on unknown columns.

Instructions

Read one column across every row of a DataTable as ExportText strings, so TMaps, soft references and tags come out flat and intact; read-only. Returns row_struct, row_count and values as {row_name: text}. Use it to verify cell edits; an unknown column is an error.

Returns: { table_path, column, row_struct, row_count, values:{ rowName: exporttext-string } }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
columnYesName of the column (a field of the row struct, by property or display name) to read across every row
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. Changed4 schema fields changedv1.2.0
    • changedInput schema / properties / column / description
      Previous value: -"Name of the column (a field of the row struct) to read across every row"New value: +"Name of the column (a field of the row struct, by property or display name) to read across every row"
    • 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."
    • changedInput schema / required
      Previous value: -[
-  "table_path",
-  "column"
-]New value: +[
+  "column"
+]
  2. First observedv1.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover read-only/idempotent/non-destructive safety. The description adds valuable behavioral detail beyond that: ExportText flattening for TMaps, soft references and tags; error behavior on unknown columns; and the returned data shape. It does not cover permissions or rate limits, but those are likely irrelevant here.

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-loaded with the core action and scoping, and compact overall. There is some redundancy: the return value summary appears twice, once briefly and once in full, so the first return sentence does not fully earn its place.

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

Completeness5/5

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

For a read-only column reader with 100% schema coverage and rich annotations, the description is complete. It states output shape, error behavior, and the ExportText rationale, leaving no critical gaps for an agent to invoke it correctly.

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 baseline is 3. The description reinforces that 'column' is read across every row and that an unknown column errors, but adds no syntax or format details beyond what the schema already provides for column, table_path, and data_table alias.

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 ('Read') and resource ('one column across every row of a DataTable'), including the output representation ('ExportText strings') and scope. This clearly distinguishes it from row-oriented siblings like get_data_table_row or get_data_table_rows.

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?

Explicitly gives a use case: 'verify cell edits'. It does not name alternative tools or exclusions, but the context for when this tool is appropriate is clear and specific.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools