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nichuan

zhenyun-pangun-mcp

by nichuan

archery_query

Execute read-only SQL queries against specified Archery database instances (CN or AWS Japan). Supports SELECT, SHOW, DESC, EXPLAIN, and WITH statements with configurable result limits.

Instructions

执行 SQL 查询(只读)。

site=cn 国内 / aws 日本云。instance 可用别名:prod/prod-ro/dev/test。 db 默认 srm。仅允许 SELECT/SHOW/DESC/EXPLAIN/WITH 前缀。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dbNo
sqlYes
siteNocn
limitNo
instanceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses read-only behavior and allowed SQL prefixes, and gives site/instance aliases. However, it does not mention behavior like result limits, error handling, or data size implications, which are important for a query tool.

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 extremely concise (three lines), front-loaded with the core purpose, and every sentence adds value. No wasted words or redundancy.

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?

Given the tool has 5 parameters, an output schema, and no annotations, the description covers the main aspects (purpose, allowed SQL, site/instance/db defaults) but omits the limit parameter and does not explain how to interpret the output or handle errors. This leaves some gaps in completeness.

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?

With 0% schema description coverage, the description compensates well by explaining the site parameter (cn vs aws), instance aliases (prod/prod-ro/dev/test), db default (srm), and the sql parameter (allowed prefixes). The limit parameter is not mentioned, but overall the description adds significant meaning beyond the bare schema.

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 'Execute SQL query (read-only)' and specifies allowed SQL prefixes (SELECT/SHOW/DESC/EXPLAIN/WITH), making the purpose clear. However, it does not explicitly differentiate from sibling tools like archery_describe_table or archery_list_databases, though the context implies this is for arbitrary read-only queries.

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 usage context (site, instance aliases, default db, allowed SQL prefixes) but does not explicitly state when to use this tool versus alternatives. It implies it's for custom read-only queries, but lacks direct guidance on alternatives or when not to use it.

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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