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dbecho

dbecho

by ginkida
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

schema

Retrieve the complete schema of a database including tables, columns, data types, primary keys, row counts, and sizes.

Instructions

Get the full schema of a database: tables, columns, types, primary keys, row counts, and sizes.

Args: database: Name of the database from config (use list_databases to see available).

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": {
      "database": "<database>"
    },
    "name": "schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
databaseYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.3/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the burden. It correctly indicates a read operation ('Get') with no destructive hints. However, it does not mention any potential size limits, performance impacts, or authentication requirements.

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 long, with the purpose stated upfront. Every sentence adds value: the first specifies what the tool returns, the second explains the parameter usage. No unnecessary words.

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?

The description specifies the return content (tables, columns, types, primary keys, row counts, sizes) without needing to duplicate an output schema. It also references a sibling tool (list_databases) for prerequisite info. Given the tool's complexity, this is fully adequate.

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?

Although the input schema itself has no parameter description (coverage 0%), the tool description explicitly documents the parameter: 'database: Name of the database from config (use list_databases to see available).' This adds meaning beyond the schema's type-only definition.

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 'Get the full schema of a database' with specific components (tables, columns, types, primary keys, row counts, sizes). This verb+resource clarity distinguishes it from siblings like list_databases (which lists database names only) and query (which runs queries).

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 implicitly advises using list_databases first to see available databases, providing a clear usage context. No explicit when-not or alternative tools for similar tasks, but for this simple informational tool, the guidance is sufficient.

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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