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stata_inspect_data

Inspect Stata datasets by running describe, summarize, or codebook on selected variables, returning cleaned output and structured summaries.

Instructions

查看当前数据:describe/summarize/codebook,可限定变量名列表。 返回命令的清洗输出;summarize(单变量)或 describe 附结构化结果。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionNodescribe: 变量清单(短版);summarize: 描述统计;codebook: 变量编码簿(compact)。describe
variablesNo要查看的 Stata 变量名列表;省略/空列表 = 全部变量。名字须为合法 Stata 变量名(字母/下划线开头,长度 1–32)。
session_idNo会话标识;省略用 'default'。

Schema Changelog

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

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are present, so the description must carry the burden. It discloses output behavior: cleaned output, and structured results for summarize/describe. The word '查看' (view) implies read-only inspection, but the description does not explicitly state non-modification, prerequisites like loaded data, or how session_id affects behavior.

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?

Two short sentences with no filler. The core purpose is front-loaded ('查看当前数据'), followed by the available actions and output characteristics. Every phrase contributes useful information.

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 3-parameter tool with no output schema, the description plus a complete schema covers the purpose, parameters, and return behavior adequately. Minor ambiguities remain around '清洗输出' and the exact meaning of 'summarize(单变量)', but they do not prevent correct invocation.

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 adds little beyond the schema; '可限定变量名列表' mirrors the variables parameter, and the action enum is fully documented in the schema with clear per-option explanations.

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 tool lets you 'inspect current data' via describe/summarize/codebook with an optional variable list. The output note about cleaned and structured results helps distinguish it from a generic command runner like stata_run, though it does not explicitly name sibling tools.

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?

The opening phrase '查看当前数据' gives a clear usage context: use this when you need to inspect the current dataset. The three enumerated actions define its scope. However, it does not mention when not to use it or suggest alternatives like stata_run for arbitrary commands.

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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