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Gakuji3

csv-analyzer-mcp

by Gakuji3

analyze_csv

Compute comprehensive statistics from CSV files: row/column counts, data types, numeric metrics (min, max, mean, std, median), unique values, missing data, and memory usage. Returns a formatted report.

Instructions

CSVファイルを分析して基本統計情報を返します。

このツールは以下の包括的な統計を計算します:

  • 行数と列数

  • 列名とデータ型

  • 数値列の場合: 最小値、最大値、平均値、標準偏差、中央値

  • 文字列列の場合: ユニーク値の数

  • 全体統計: 欠損値の合計、メモリ使用量

Args: file_path: 分析対象の CSV ファイルへの絶対パスまたは相対パス 例: "/path/to/data.csv" または "data.csv"

Returns: 統計情報と洞察を含むフォーマット済みのテキストレポート ファイルが読み込めない場合または空の場合はエラーメッセージを返します

Example: >>> await analyze_csv("/Users/username/data.csv") # フォーマット済みの統計レポートを返します

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral disclosure burden. It details exactly which statistics are computed, states that the return is a formatted text report, and specifies error conditions for unreadable or empty files. It does not cover potential size limits or encoding concerns, but for a read-only analysis tool this is solid coverage.

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?

The description is well-structured with a clear purpose statement, a bulleted list of statistics, an Args section, a Returns section, and an example. Every element contributes value and there is no redundancy, making it 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?

Given the output schema exists (signal true), the description does not need to detail return fields. It covers input semantics, output format, error behavior, and an example, so an agent can invoke it correctly. The only notable gap is the lack of routeing relative to the sibling tool get_csv_summary.

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

Parameters4/5

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

The input schema has 0% coverage, so the description must define file_path. It does so clearly, explaining that it accepts absolute or relative paths and providing a concrete example. This is useful beyond the raw schema, though it stops short of mentioning supported file extensions or size constraints.

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 clearly states the verb ('analyze'), the resource ('CSV file'), and the outcome ('basic statistical information'). However, it does not mention the sibling tool get_csv_summary or explain how it differs, so an agent must infer the distinction.

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?

The description includes an example invocation and describes the file_path argument, but gives no explicit guidance about when to use this tool versus get_csv_summary, nor any conditions or exclusions. The usage context is entirely implicit.

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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