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IA-QA — 152 QA & Dev Tools for AI Agents

by io.github.JcJamet
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parse_csv

Read-onlyIdempotent

Parse a CSV string into a JSON array of objects (or raw arrays). Full RFC 4180: quoted fields may contain the delimiter, embedded newlines (the Excel/Sheets multi-line cell), and doubled quotes. Custom delimiters supported. An unterminated quote is rejected with its position rather than parsed into corrupted rows. Use when processing spreadsheet exports, data imports, or structured text pipelines where the source is CSV. Supports up to 200 KB.

Input Schema

NameRequiredDescriptionDefault
inputYesCSV content to parse
headerNoTreat the first row as headers (default: true)
delimiterNoField delimiter character (default: ",")

Output Schema

NameRequiredDescriptionDefault
rowsNo
columnsNo
headersNo
row_countNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "delimiter": ";",
+    "input": "a;b\n1;2"
+  }
+]
  2. Changed1 schema field changed
    • addedOutput schema / properties
      Added value: +{
+  "columns": {
+    "type": "number"
+  },
+  "headers": {
+    "type": "array"
+  },
+  "row_count": {
+    "type": "number"
+  },
+  "rows": {
+    "type": "array"
+  }
+}
  3. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "type": "object"
+}
  4. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive, closed-world semantics. The description adds genuinely new context: full RFC 4180 handling, quoted fields with embedded newlines/doubled quotes, unterminated-quote rejection with position info, and a 200 KB size cap. Only the exact error/return shape is left implicit, which the output schema covers.

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?

Five tight sentences, front-loaded with the core contract, then RFC details, then error behavior, then usage guidance. No filler or redundancy.

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 small, read-only 3-parameter tool with an output schema and full parameter coverage, the description supplies the key behavioral facts (RFC 4180 compliance, multi-line cells, error-on-unterminated-quote, size limit). Nothing critical is missing, though a note on how parse errors surface would close the last gap.

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 coverage is 100%, including defaults for header and delimiter, so the schema carries the parameter documentation. The description only echoes custom delimiter support and never mentions the header flag, so no meaningful value is added beyond the schema.

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 (parse) and resource (CSV string) and immediately names the output form (JSON array of objects or raw arrays). This is clearly distinguishable from siblings like json_to_csv, which converts the other direction.

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?

Gives concrete usage context: spreadsheet exports, data imports, structured text pipelines where the source is CSV. It does not explicitly rule out or point to alternatives (e.g., json_to_csv for the inverse direction), so it falls just short of a 5.

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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