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ToolForte

CSV to JSON

csv_to_json
Read-onlyIdempotent

Parse CSV data into JSON with delimiter auto-detection and quoted-field handling.

Input Schema

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

Output Schema

TableJSON 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

A3.8/5.0
Behavior4/5

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

Annotations already carry the full safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds real behavioral detail beyond that: automatic delimiter detection and quoted-field handling. It says nothing about failure behavior on malformed CSV or the size cap, which is the only remaining gap.

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 tight sentence with the core operation front-loaded and no filler. Every clause earns its place by naming a distinct capability.

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?

For a two-parameter, single-purpose converter with an output schema and complete annotations, the description covers what an agent needs. Only edge-case behavior (malformed input, empty CSV, size limit) is unaddressed, which is minor.

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 the baseline is 3. The description's mention of auto-detection duplicates the schema's own note on the csv parameter and adds no new syntax, format, or default information for firstRowHeaders.

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 and resource ('Parse CSV data into JSON') plus two concrete capabilities (delimiter auto-detection, quoted-field handling), which is enough to separate it from siblings like format_json. It never names a sibling or explicitly excludes them, so it falls short of the top mark.

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

Usage Guidelines3/5

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

The description implies the use case (raw CSV text goes in, JSON comes out) but gives no explicit when-to-use guidance, no prerequisites, and no mention of the nearest alternative, format_json. Usage is inferable rather than stated.

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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