Skip to main content
Glama
jovian-zhibai

mcp-database

diagnose_connection

Diagnose database connection issues by returning detailed status and troubleshooting hints for a specified connection. Use this to identify and resolve connectivity problems.

Instructions

Diagnose a database connection with detailed status and troubleshooting hints.

Args: connection_name: Name of the database connection (default: "default").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
connection_nameNodefault

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the output includes status and troubleshooting hints, but does not state whether the operation is read-only, whether it requires credentials, makes network calls, or is safe to run in production. These are significant gaps for a diagnostic 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 two sentences with no wasted words, front-loading the core purpose before the parameter details. It is compact and directly maps to the schema without 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?

For a tool with one optional parameter and an output schema, the description is mostly adequate: it states the purpose and the parameter meaning. However, it omits any usage context or relationship to sibling tools, and the absence of annotations leaves behavioral gaps. Despite the simple interface, these omissions prevent a higher score.

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 description coverage is 0%, so the description's 'Args' section is the only source of parameter meaning. It adds 'Name of the database connection' and the default, which is sufficient for the single optional parameter, but this adds little beyond the schema's title and default value.

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 the tool diagnoses a database connection and provides 'detailed status and troubleshooting hints,' giving a specific verb and resource. However, it does not differentiate itself from sibling tool check_health, which may also inspect connection health, so it does not earn a 5.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to use this tool instead of alternatives like check_health or list_databases. The word 'diagnose' implies a troubleshooting context, but no when-to-use, prerequisites, or exclusions are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.