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Read file columns

read_file_columns
Read-only

The column headings of an uploaded CSV, and how many rows are under them. Read this before folding a column, so you name one that is actually there. To read the rows themselves, or a workbook or a PDF, use read_file_rows.

Input Schema

NameRequiredDescriptionDefault
fileidYesThe file to read.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

readOnlyHint=true is already declared, so the safety profile is covered by annotations; the description adds that the output is headings plus per-column row counts and that the tool is scoped to CSV uploads rather than workbooks or PDFs. It does not say what happens if the fileid is not a CSV or is unreadable, which would be the remaining behavioral gap.

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?

Three short sentences, with the return value front-loaded and routing to the sibling last; nothing is filler. The fragmentary opening sentence and the slightly colloquial 'so you name one that is actually there' cost it a point on polish rather than on length.

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 does the necessary work of describing the return value (column headings and their row counts) and the input constraint (CSV uploads only), and it names the correct sibling for other cases. Handling of malformed or non-CSV fileids is the one thing an agent could still be surprised by.

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

Parameters4/5

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

Schema coverage is 100% but the schema only says 'The file to read', which is generic; the description narrows that to an uploaded CSV and implicitly excludes workbooks and PDFs, adding real meaning about what a valid fileid is. It does not describe identifier format (id vs. path), so it stops short of a 5.

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?

It states exactly what the tool returns – the column headings of an uploaded CSV plus the row count under each – and explicitly tells the agent it is not the row reader, pointing at read_file_rows for that. It lacks a leading verb ('list'/'read') and the first sentence is a noun fragment, which keeps it just below a 5.

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?

It gives a concrete precondition ('read this before folding a column, so you name one that is actually there') and names the alternative tool with the conditions that select it (rows, workbooks, PDFs → read_file_rows). An agent can decide between this tool and the sibling without opening any schema.

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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