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CSV to Chart

csv-chart

Turn CSV into a chart. Input: csv (first row = headers). Returns headers, row count and numeric columns. The card renders a bar/line chart.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
csvYes
localeNoen

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose return content ('headers, row count and numeric columns') and the rendering behavior, which is genuine added context. However, it says nothing about malformed CSV, non-numeric columns, missing required input, or size limits — notable gaps for a parse-and-render tool.

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?

Three short sentences, front-loaded with the core action, then input format, then return shape. No filler and every clause carries information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description does reasonably well: it covers the input format and the key return fields. But the silent `locale` parameter and the absence of any failure-mode or size-limit context leave meaningful gaps for a tool that must parse arbitrary CSV.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It documents `csv` partially ('first row = headers') but never mentions the `locale` parameter (enum en/zh) that appears in the schema, leaving half the parameters semantically unexplained anywhere.

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 opens with a specific verb+resource: 'Turn CSV into a chart.' That is unambiguous and distinguishable from siblings like echarts or function-grapher, which operate on different inputs. It stops short of explicitly naming which sibling to use instead, so it lands at a clear-but-not-differentiating 4.

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

Usage Guidelines2/5

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

There is no when-to-use guidance and no routing to alternatives such as echarts, function-grapher or statistics, all of which could plausibly consume structured data. The mention that 'the card renders a bar/line chart' implies display context but does not tell an agent when this tool is the right choice versus a sibling.

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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