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text_text_column

Need to extract columns from delimited text? This tool extracts, aligns, and analyzes columnar data from CSV, TSV, and space-separated formats.

Instructions

Menu ID: text_text_column. Text Column Tool. Extract columns from delimited text, align columnar data, and analyze column structure. Perfect for processing CSV, TSV, and space-separated data. Use describe_tool with tool_id "text_text_column" for full page guidance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
operationYes
columnNumberYes
delimiterYes
alignmentYes
widthYes
fillCharYes
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It barely mentions extract, align, analyze but does not detail that all 7 parameters are required, what operations are available, error handling, or side effects. The deferral to describe_tool indicates incomplete transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

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

The description is short but includes a redundant 'Menu ID' line that adds no value. The structure is okay but could be more compact. It front-loads the main purpose but wastes space on administrative info.

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

Completeness1/5

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

Given 7 required parameters, no output schema, and 0% schema coverage, the description is critically incomplete. It does not specify return format, required order, or valid values. The prompt to use describe_tool suggests the description alone is insufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It mentions general functions (extract, align, analyze) but does not explain parameters like text, operation, columnNumber, delimiter, alignment, width, fillChar. Without parameter details, the agent cannot infer usage.

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 it extracts columns, aligns data, and analyzes column structure from delimited text. It specifies CSV, TSV, and space-separated formats, which is specific and distinguishes it from sibling tools (no other column tool exists).

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

Usage Guidelines3/5

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

The description suggests it is 'perfect for processing CSV, TSV, and space-separated data,' giving some usage context. However, it lacks guidance on when not to use it or alternatives, and defers to describe_tool for more info, which is a limited guideline.

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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