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Convert table

convert_table
Read-onlyIdempotent

Convert a table from CSV, TSV or JSON into CSV, TSV, JSON (array of objects) or a Markdown table. Cell values are kept as text. Use when the user wants the same table in another format. Do NOT use to trim, dedupe or drop rows; use clean_table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe whole table as text, first row = header. CSV/TSV text (quoted cells allowed), or a JSON array of flat objects, e.g. "name,age\nAsha,30".
to_formatYesOutput format: csv, tsv, json (array of objects keyed by header) or markdown (pipe table).
from_formatYesFormat of the input 'data': csv, tsv or json.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYesNumber of data rows (excluding the header).
textYesThe converted table as text in to_format.
columnsYesNumber of columns in the header row.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed13 schema fields changed
    • changedInput schema / properties / data / description
      Previous value: -"The data for this request."New value: +"The whole table as text, first row = header. CSV/TSV text (quoted cells allowed), or a JSON array of flat objects, e.g. \"name,age\\nAsha,30\"."
    • addedInput schema / properties / data / minLength
      Added value: +1
    • changedInput schema / properties / from_format / description
      Previous value: -"The from format for this request."New value: +"Format of the input 'data': csv, tsv or json."
    • addedInput schema / properties / from_format / enum
      Added value: +[
+  "csv",
+  "tsv",
+  "json"
+]
    • changedInput schema / properties / to_format / description
      Previous value: -"The to format for this request."New value: +"Output format: csv, tsv, json (array of objects keyed by header) or markdown (pipe table)."
    • addedInput schema / properties / to_format / enum
      Added value: +[
+  "csv",
+  "tsv",
+  "json",
+  "markdown"
+]
    • addedOutput schema / properties / columns
      Added value: +{
+  "description": "Number of columns in the header row.",
+  "type": "integer"
+}
    • removedOutput schema / properties / converted_data
      Removed value: -{
-  "description": "The table data converted to the specified format.",
-  "type": "string"
-}
    • removedOutput schema / properties / from_format
      Removed value: -{
-  "description": "The original format of the table data.",
-  "type": "string"
-}
    • addedOutput schema / properties / rows
      Added value: +{
+  "description": "Number of data rows (excluding the header).",
+  "type": "integer"
+}
    • addedOutput schema / properties / text
      Added value: +{
+  "description": "The converted table as text in to_format.",
+  "type": "string"
+}
    • removedOutput schema / properties / to_format
      Removed value: -{
-  "description": "The format the table data was converted to.",
-  "type": "string"
-}
    • changedOutput schema / required
      Previous value: -[
-  "converted_data",
-  "from_format",
-  "to_format"
-]New value: +[
+  "text",
+  "rows",
+  "columns"
+]
  2. Changed3 schema fields changed
    • addedInput schema / properties / data / description
      Added value: +"The data for this request."
    • addedInput schema / properties / from_format / description
      Added value: +"The from format for this request."
    • addedInput schema / properties / to_format / description
      Added value: +"The to format for this request."
  3. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "converted_data": {
+      "description": "The table data converted to the specified format.",
+      "type": "string"
+    },
+    "from_format": {
+      "description": "The original format of the table data.",
+      "type": "string"
+    },
+    "to_format": {
+      "description": "The format the table data was converted to.",
+      "type": "string"
+    }
+  },
+  "required": [
+    "converted_data",
+    "from_format",
+    "to_format"
+  ],
+  "type": "object"
+}
  4. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: 'Cell values are kept as text', which tells the agent no type coercion or numeric parsing occurs. It stops short of describing malformed-input or header-handling behavior, so it is not exhaustive.

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, front-loaded with the conversion scope before the usage guidance and exclusion. The format enumeration partially duplicates the schema's enum descriptions, which is a minor redundancy, but every sentence still carries selection value.

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?

An output schema exists so return values need no explanation, and the annotations already cover the safety profile. What remains — what the tool does, when to use it, when not to, and what happens to cell values — is all present, leaving no meaningful gap for a 3-parameter conversion tool.

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% and both format parameters carry their own enum descriptions, so the schema does the heavy lifting — baseline 3. The description restates the accepted format sets but adds no syntax, default, or edge-case detail beyond what the schema already documents.

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 ('Convert') and resource ('a table'), then enumerates both input and output formats explicitly. It also names the sibling clean_table and the exact operations that belong to it, so an agent can distinguish this tool from its alternatives without opening any 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 an affirmative trigger ('Use when the user wants the same table in another format') and an explicit exclusion with an alternative ('Do NOT use to trim, dedupe or drop rows; use clean_table'). Nothing about tool selection is left to inference.

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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