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bluebonnet-sales

bluebonnet-sales

by hostedinthebarn
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

run_query

Read-only

Safely run read-only SQL SELECT queries against the sales database to answer business questions, returning up to 200 rows with a 5-second limit.

Instructions

Run one read-only SQL SELECT and return up to 200 rows.

Anything that would change data, attach another database or change settings is refused. Queries are stopped after 5 seconds.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "sql": "<sql>"
    },
    "name": "run_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
sqlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior5/5

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

Annotations cover only read-only/open-world; the description adds real operational traits: a hard 200-row return cap, a 5-second execution cutoff, and the exact class of statements that will be refused. Those are the failure modes an agent most needs to know before calling.

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?

Three short sentences, each carrying a distinct constraint (row cap, refusal policy, timeout), with the primary purpose front-loaded. Nothing is filler.

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?

With no output schema, the description usefully states the return size ('up to 200 rows') and the operational envelope. It leaves gaps on dialect and error/refusal messaging, but for a one-parameter query tool it is nearly 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 coverage is 0% and the single 'sql' parameter has no description, so the description must compensate. It does partially – 'one ... SQL SELECT' implies single-statement, SELECT-only input – but says nothing about SQL dialect, semicolons, or how the 200-row cap interacts with LIMIT.

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?

States a specific verb+resource ('Run one read-only SQL SELECT') with the output cap attached, so the agent knows exactly what it does. It doesn't name the sibling tools (sales_summary, list_tables), so the distinction from the canned-query siblings is only implicit.

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 refusals ('anything that would change data, attach another database or change settings') tell the agent when-not to use it, and the 5s timeout implies 'keep queries narrow'. But it never routes the agent to siblings like sales_summary or top_customers for common queries, leaving the choice 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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