Convert CSV data into a JSON array of objects, handling custom delimiters, header detection, and quoted fields.
Convert CSV data to a JSON array of objects. Supports custom delimiters, header detection, and quoted fields.
| Name | Required | Description | Default |
|---|---|---|---|
| csv | Yes | CSV content as a string | |
| delimiter | No | Column delimiter: comma, semicolon, tab, or pipe (default: comma) | |
| has_headers | No | First row contains column headers (default: true) |
Changes observed during successful MCP inspections.
v1.4.2Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true and openWorldHint=false, which cover the safety and determinism profile. The description adds useful capabilities (custom delimiters, header detection, quoted fields), but does not disclose error behavior, encoding assumptions, or edge-case handling. With annotations present, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that states the core action, output format, and distinctive capabilities. Every phrase adds value, and there is no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple conversion utility with only one required parameter and a readable input schema. The description plus schema covers the essential operation. It doesn't explain return values or error handling, but given the obvious output type and read-only annotation, nothing critical is missing for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters. The description mentions custom delimiters and header detection, which map to delimiter and has_headers, but adds no meaning beyond what the schema descriptions provide. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Convert') and resource ('CSV data') with an explicit output ('JSON array of objects'). It also names key capabilities (delimiters, header detection, quoted fields) that clearly distinguish this tool from inverse or formatting siblings like json_to_csv and format_json.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied: use it when you need to transform CSV into JSON. However, there is no explicit statement about when not to use it or which sibling alternative (e.g., json_to_csv) handles the reverse operation. No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.