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TGich

dm_mcp_server

by TGich

batch_comment_columns_sql

Execute multiple COMMENT ON COLUMN statements in a single batch to add column comments. Optionally stop on error for controlled execution.

Instructions

批量执行字段注释 SQL,仅允许 COMMENT ON COLUMN 语句

参数: sql: 多条 COMMENT ON COLUMN 语句,可用分号分隔 stop_on_error: 执行阶段遇到错误是否停止

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYes
stop_on_errorNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv2.6.2

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral disclosure burden. It discloses the core restriction and that stop_on_error controls whether execution halts on error, but it does not explain what happens with invalid statements, whether execution is transactional, or what side effects occur beyond modifying column comments.

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 compact and front-loaded: a one-sentence purpose plus a short parameter list. Every sentence contributes useful information with no filler or repetition.

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?

It covers the main purpose and both parameters, and an output schema exists so return-value documentation is less critical. However, with no annotations, a batch SQL-writing tool would benefit from more context about validation behavior, error handling for disallowed statements, and transaction or rollback semantics.

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?

Schema description coverage is 0%, so the parameter explanations in the description are essential. They add real meaning: sql is defined as multiple COMMENT ON COLUMN statements separated by semicolons, and stop_on_error is described as whether to stop when encountering errors during execution. This meaningfully exceeds the bare schema.

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 identifies a specific verb and resource: it batch-executes field comment SQL and explicitly restricts execution to COMMENT ON COLUMN statements. This distinguishes it from broad siblings like execute_sql and execute_sql_file.

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 allowed statement type is stated ('仅允许 COMMENT ON COLUMN 语句'), which implies when the tool is appropriate. However, it does not explicitly mention alternatives such as execute_sql or explain when not to use this tool, leaving sibling selection mostly 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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