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mcp-yearning

by zhouweico
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Hybrid

yearning_sql_check

Read-onlyIdempotent

Audit SQL before submission to catch errors, estimate affected rows, and measure execution time. Get per-statement results to ensure safety before creating an order.

Instructions

提交前对 SQL 做审核检测，返回逐条检查结果（级别/影响行数/错误/执行耗时）。

建议先调用本工具确认无误，再调用 yearning_submit_order 提交工单。 对应 API：PUT /api/v2/fetch/test

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYes待检测的 SQL
databaseYes库名
source_idYes数据源 ID
order_typeYesSQL 类型：ddl / dml
response_formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed8 schema fields changedv0.3.0
    • removedInput schema / $defs / SqlCheckInput
      Removed value: -{
-  "additionalProperties": false,
-  "properties": {
-    "database": {
-      "description": "库名",
-      "title": "Database",
-      "type": "string"
-    },
-    "order_type": {
-      "$ref": "#/$defs/OrderType",
-      "description": "SQL 类型：ddl / dml"
-    },
-    "response_format": {
-      "$ref": "#/$defs/ResponseFormat",
-      "default": "markdown"
-    },
-    "source_id": {
-      "description": "数据源 ID",
-      "title": "Source Id",
-      "type": "string"
-    },
-    "sql": {
-      "description": "待检测的 SQL",
-      "title": "Sql",
-      "type": "string"
-    }
-  },
-  "required": [
-    "source_id",
-    "database",
-    "sql",
-    "order_type"
-  ],
-  "title": "SqlCheckInput",
-  "type": "object"
-}
    • addedInput schema / properties / database
      Added value: +{
+  "description": "库名",
+  "title": "Database",
+  "type": "string"
+}
    • addedInput schema / properties / order_type
      Added value: +{
+  "$ref": "#/$defs/OrderType",
+  "description": "SQL 类型：ddl / dml"
+}
    • removedInput schema / properties / params
      Removed value: -{
-  "$ref": "#/$defs/SqlCheckInput"
-}
    • addedInput schema / properties / response_format
      Added value: +{
+  "$ref": "#/$defs/ResponseFormat",
+  "default": "markdown"
+}
    • addedInput schema / properties / source_id
      Added value: +{
+  "description": "数据源 ID",
+  "title": "Source Id",
+  "type": "string"
+}
    • addedInput schema / properties / sql
      Added value: +{
+  "description": "待检测的 SQL",
+  "title": "Sql",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "params"
-]New value: +[
+  "source_id",
+  "database",
+  "sql",
+  "order_type"
+]
  2. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is clear. The description adds behavioral context by detailing return values (check results with level/affected rows/errors/execution time) and the API endpoint (PUT /api/v2/fetch/test), which goes beyond the structured annotations. No contradictions with annotations exist.

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 two sentences: first sentence states purpose and output, second provides usage recommendation and API. It is front-loaded, concise, and every sentence contributes useful information. No waste or redundancy.

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 tool's moderate complexity, the description covers purpose, usage, output characteristics, and API endpoint. An output schema exists, so return details needn't be fully explained. The description is sufficient for an agent to select and invoke this tool correctly, though it could optionally mention any limitations or prerequisites.

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 coverage is 80% with descriptions for sql, database, source_id, and order_type. The description does not add parameter-specific semantics beyond that; it only mentions "逐条检查结果" (per-item results), which relates to output, not parameters. With high schema coverage, baseline 3 is appropriate.

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 tool performs a pre-submission SQL audit check ("提交前对 SQL 做审核检测") and specifies the output includes per-item results (level/affected rows/errors/execution time). This distinguishes it from sibling tools like yearning_run_query, which likely executes queries rather than validating them. The reference to yearning_submit_order further clarifies its role in the workflow.

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 description explicitly recommends calling this tool before yearning_submit_order ("建议先调用本工具确认无误，再调用 yearning_submit_order 提交工单"), providing clear when-to-use guidance. It lacks explicit when-not-to-use or alternative tool mentions, but the workflow context is strong enough for an agent to infer appropriate usage.

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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