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Trustbase Lab · Trusted Data Infrastructure for the AI Era

Database Overview

get_database_overview
Read-onlyIdempotent

Purpose: dataset overview - version, record counts per table, entity-ID rules (stable IDs like rcb-cn-001, append-only), confidence grading (A/B/C), verified-supplier counts, the full tool index and site module map. Guidelines: call this FIRST when discovering the server, then route to specific query_* tools; pass language='en' for English output, response_format='json' for Agent processing. Limits: metadata only - no record content; counts refresh with each data release (schema 1.10). Ex: 'what data does this server have', 'list available tools'.

Input Schema

NameRequiredDescriptionDefault
languageNo输出语言 / output languagezh
response_formatNo输出格式:markdown=人类阅读, json=Agent 处理友好markdown

Output Schema

NameRequiredDescriptionDefault
textYesHuman-readable result (markdown, or a JSON string when response_format=json).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "additionalProperties": true,
      +  "properties": {
      +    "text": {
      +      "description": "Human-readable result (markdown, or a JSON string when response_format=json).",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "text"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive and closed-world, so the safety profile is covered. The description adds real behavioral context beyond that: 'metadata only - no record content' and 'counts refresh with each data release' tell the agent what it will and won't get and that counts are release-dependent.

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?

Organized with Purpose/Guidelines/Limits/Ex labels so the key routing instruction is front-loaded and scannable. Every clause adds information (payload contents, routing, limits, examples) with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value detail is unnecessary, and the description still states its metadata-only scope and refresh behavior. For a read-only overview tool with two optional, well-documented enum params, nothing an agent needs to call it correctly is missing.

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 100% with enums and defaults already documented, so the schema carries the parameter burden. The description echoes the intended usage ('language=en', 'response_format=json for Agent processing'), which is a light reinforcement but largely restates what the schema description already says, landing at the 3 baseline.

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?

States a specific verb and resource (dataset overview) and enumerates the payload: version, per-table record counts, entity-ID rules, confidence grading, supplier counts, tool index, module map. It clearly distinguishes itself from the query_* siblings by framing itself as the discovery entry point rather than a data query.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to call this FIRST when discovering the server, then route to specific query_* tools, which tells the agent both when to use it and which alternatives to use afterward. It also gives example phrasings ('what data does this server have', 'list available tools') that clarify the trigger conditions.

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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