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CSV to JSON

csv_to_json
Read-onlyIdempotent

Use this when you need CSV data as JSON objects. Example prompt: "Turn this CSV export into JSON." Parse CSV data into JSON with delimiter auto-detection and quoted-field handling. Costs 1 credit. The answer is deterministic.

Input Schema

NameRequiredDescriptionDefault
csvYesThe CSV text; the delimiter is detected automatically
firstRowHeadersNoTreat the first row as column names and return objects (default true)

Output Schema

NameRequiredDescriptionDefault
jsonNo
resultNoThe result, when it is not an object
delimiterNo
row_countNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / $schema
      Removed value: -"https://json-schema.org/draft/2020-12/schema"
    • removedOutput schema / $schema
      Removed value: -"https://json-schema.org/draft/2020-12/schema"
  2. Changed3 schema fields changed
    • addedInput schema / properties / csv / description
      Added value: +"The CSV text; the delimiter is detected automatically"
    • addedInput schema / properties / firstRowHeaders / description
      Added value: +"Treat the first row as column names and return objects (default true)"
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "delimiter": {
+      "type": "string"
+    },
+    "json": {
+      "items": {},
+      "type": "array"
+    },
+    "result": {
+      "description": "The result, when it is not an object"
+    },
+    "row_count": {
+      "type": "number"
+    }
+  },
+  "type": "object"
+}
  3. Changed3 schema fields changed
    • removedInput schema / properties / csv / description
      Removed value: -"The CSV text; the delimiter is detected automatically"
    • removedInput schema / properties / firstRowHeaders / description
      Removed value: -"Treat the first row as column names and return objects (default true)"
    • changedOutput schema / (root)
      Previous value: -{
-  "$schema": "https://json-schema.org/draft/2020-12/schema",
-  "additionalProperties": {},
-  "properties": {
-    "delimiter": {
-      "type": "string"
-    },
-    "json": {
-      "items": {},
-      "type": "array"
-    },
-    "result": {
-      "description": "The result, when it is not an object"
-    },
-    "row_count": {
-      "type": "number"
-    }
-  },
-  "type": "object"
-}New value: +null
  4. Changed3 schema fields changed
    • addedInput schema / properties / csv / description
      Added value: +"The CSV text; the delimiter is detected automatically"
    • addedInput schema / properties / firstRowHeaders / description
      Added value: +"Treat the first row as column names and return objects (default true)"
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "delimiter": {
+      "type": "string"
+    },
+    "json": {
+      "items": {},
+      "type": "array"
+    },
+    "result": {
+      "description": "The result, when it is not an object"
+    },
+    "row_count": {
+      "type": "number"
+    }
+  },
+  "type": "object"
+}
  5. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description goes beyond them with genuinely useful operational facts: delimiter auto-detection, quoted-field handling, deterministic output, and a stated cost of 1 credit.

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?

The usage trigger is front-loaded and the behavioral details follow compactly. The example prompt borders on redundant with the opening sentence, but the whole definition stays short and easy to scan.

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?

An output schema exists and the parameters are fully described, so return values and inputs need no further explanation. For a two-parameter transformation tool, the description covers cost, determinism and parsing behavior adequately, with only sibling differentiation left implicit.

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%, so both parameters are already documented, and the description only echoes the auto-detection behavior that the 'csv' field description already states. It adds nothing about 'firstRowHeaders' beyond what the schema provides, so the baseline 3 applies.

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?

The description states a specific verb and resource: 'Parse CSV data into JSON' with delimiter auto-detection and quoted-field handling. This clearly distinguishes it from format_json, though the description never names the sibling, leaving the agent to infer the boundary itself.

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

Usage Guidelines4/5

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

It gives a concrete trigger ('Use this when you need CSV data as JSON objects') plus a realistic example prompt. That establishes when to use it, but there are no exclusions or named alternatives even though format_json exists in the sibling set.

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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