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Markdown table from CSV: convert CSV into a GitHub table

csv_to_markdown
Read-only

Convert CSV (comma, semicolon, tab or pipe, detected automatically; quoted fields supported) into a GitHub-flavoured Markdown table, with number columns right-aligned, pipes escaped and line breaks kept as . Up to 100 KB. Use to show spreadsheet data in a README, chat reply, issue or report; for JSON use csv_to_json. Example: csv=tool,price,calls weather,0.01,120 search,0.01,45. Price $0.01/call via x402 USDC or a card key (/credits), first 25 free; failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

Input Schema

NameRequiredDescriptionDefault
csvYesThe CSV text (up to 100 KB)
headerNotrue (default) if the first row holds the column names

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior4/5

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

Adds real behavioral detail beyond the annotations: auto-detected delimiters, quoted-field handling, a 100 KB ceiling, and explicit 'reads or computes only and changes nothing' which complements readOnlyHint/destructiveHint. The billing note ('each call is charged, first 25 free, failed calls free') is useful but slightly muddies the picture by hinting at a non-idempotent cost model rather than clarifying behavior.

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?

Conversion semantics are front-loaded in the first sentence, with usage and the sibling alternative following. The inline CSV example and the pricing sentence make it longer than strictly needed for a two-parameter tool, but every element is at least informative.

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?

No output schema exists, and the description compensates by describing the produced table's formatting rules (alignment, escaped pipes, <br>). Together with the input limits and no-side-effect statement, an agent has everything needed to call it correctly.

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%, so the baseline is 3, and the description adds value: it documents which delimiters are auto-detected and that quoted fields are supported, plus the default header behavior. It goes modestly beyond the schema rather than substantially re-explaining it.

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 and resource (convert CSV into a GitHub-flavoured Markdown table) and spells out the exact output conventions (right-aligned numbers, escaped pipes, <br> for line breaks). It explicitly names csv_to_json as the sibling for the JSON case, so an agent can route without opening either 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?

Gives concrete when-to-use scenarios (README, chat reply, issue, report) and an explicit alternative with its selection condition ('for JSON use csv_to_json'). Delimiter support and size limit further delimit applicability.

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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