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describe_file

Compute descriptive statistics for a chosen numeric column in CSV, TSV, TXT, JSON, or NPY files to inspect distributions and data quality.

Instructions

Describe one numeric column of a CSV/TSV/TXT/JSON/NPY file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
columnNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries full disclosure burden. It does not state what statistics or summary is returned, whether the operation is read-only, what happens for missing/non-numeric columns, or any file-size/parsing caveats.

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?

A single sentence with zero filler, and the core scope ('one numeric column') is front-loaded. It is appropriately sized for a short description.

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

Completeness2/5

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

For a file-parsing/statistics tool with no annotations, no output schema, and 0% parameter documentation, the description is far too thin. An agent lacks enough information about column selection, return values, or supported behavior to call it confidently.

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 only vaguely mentions 'one numeric column' and file types, but never explains that 'column' accepts a name or index, what happens when it is omitted (default null), or what the required 'path' should point to.

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?

States a specific verb ('Describe') and resource ('one numeric column of a CSV/TSV/TXT/JSON/NPY file'), which is more precise than the generic sibling 'describe'. However, it does not differentiate itself from that sibling, leaving an agent to guess which one to use.

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?

No guidance on when to use this tool versus alternatives like 'describe', 'distribution', or 'analyze_dataset'. The only implied usage is inferring from file formats, which is weak context.

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