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joyous-coder

universal-db-mcp

by joyous-coder

import_csv

Import rows from a CSV file into an existing table in append mode, with options for dry run, column selection, batch size, header, and null strings. Requires write permission.

Instructions

从 CSV 文件导入数据到已存在的表 (APPEND 模式)。需 write 权限。profileName 可选 — 省略时使用当前活跃连接。[group: data-governance]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYes
dryRunNo
columnsNo
filePathYes
batchSizeNo
hasHeaderNo
nullStringsNo
profileNameNo可选。省略则使用当前活跃连接。

Schema Changelog

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

  1. First observedv5.0.2

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It does disclose important behavior: append mode (not overwrite), write permission requirement, and current active connection fallback for profileName. However, it does not explain side effects, atomicity, error behavior, or return values, which are significant for an importing/mutating tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded with the core action, followed by permission and profile behavior. All sentences contribute information, though the trailing [group: data-governance] tag adds little for an agent interpreting the tool.

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

Completeness2/5

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

For an 8-parameter data import tool with no annotations and no output schema, the description is too thin. It omits guidance on key parameters like dryRun, columns, hasHeader, nullStrings, and batchSize, and does not describe expected results or failure modes.

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 only 13%, so the description needed to compensate. It only provides context for profileName, which is already described in the schema, and says nothing meaningful about table, filePath, dryRun, columns, batchSize, hasHeader, or nullStrings.

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?

The description clearly states the action (import), source (CSV file), target (existing table), and mode (APPEND). This distinguishes it from sibling tools like export_table_csv and import_profiles by specifying resource and operation.

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

Usage Guidelines3/5

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

The description provides useful context: it appends to an existing table, requires write permission, and profileName is optional. However, it does not explicitly state when to use this tool versus alternatives, such as import_profiles or other import mechanisms, leaving that to inference.

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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