Skip to main content
Glama
rubyLs

@rubyls/yearning-mcp

by rubyLs

提交 SQL 工单

yearning_submit_order

Submit SQL change orders (DDL/DML) to Yearning for approval, requiring an explicit confirmation to finalize submission and start the audit workflow.

Instructions

提交 SQL 工单(DDL/DML)。提交前建议先 yearning_sql_check。对应 POST /api/v2/common/post。必须传 confirm=true 才会真正提交。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYes完整 SQL 语句
delayNo延时执行时间,如 2026-01-01 02:00
tableNo影响表名(可选)
backupNo是否备份:0 否 / 1 是(DML 建议开启)
remarkYes工单说明
confirmYes必须为 true,确认提交工单进入审核流程
assignedNo期望审核人(提示用;实际以流程模板为准)
databaseYes目标库名
source_idYes数据源 ID
order_typeYes工单类型
execute_timeNo执行时间(可选)
Behavior4/5

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

Adds context beyond annotations: mentions the API endpoint POST /api/v2/common/post and requires confirm=true to truly submit, implying a confirmation guard. It doesn't contradict readOnlyHint=false or destructiveHint=false, and adds the pre-check recommendation.

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?

Four short sentences each add value: purpose, pre-check recommendation, API mapping, and confirm requirement. No redundant text, and it is front-loaded with the core purpose.

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?

The description plus schema provides enough to invoke: confirm requirement and all parameters are documented. It omits return value but no output schema exists; still, for a mutation tool with 11 params, it is reasonably complete.

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 covers all 11 parameters with descriptions (100% coverage). Description only highlights confirm=true, which is already in the schema, adding no new parameter semantics.

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?

Description clearly states it submits SQL work orders for DDL/DML, using the verb '提交' (submit) and resource 'SQL工单'. It distinguishes from sibling yearning_submit_query_order by specifying DDL/DML, making its purpose unambiguous.

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?

Explicitly recommends running yearning_sql_check before submission and mandates confirm=true for actual submission. This gives clear when-to-use guidance, though it doesn't explicitly list alternatives like yearning_submit_query_order.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rubyLs/yearning_mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server