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Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

database_status

Read-only

Checks whether Kiln uses SQLite or PostgreSQL, reports connection status and key metrics, and helps verify migrations or diagnose database connectivity issues.

Instructions

Check database backend status and configuration.

Reports whether Kiln is using SQLite or PostgreSQL, the connection status, and key metrics. Useful for verifying a PostgreSQL migration or diagnosing connectivity issues.

Requires Enterprise license.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "database_status"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and non-destructive behavior, so the safety profile is covered. The description adds genuinely new context, most importantly the Enterprise license prerequisite and the fact that it distinguishes backend types, which an agent could not infer from structured fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded single-purpose statement followed by the specifics and the licensing caveat; every sentence carries information. The only blemish is the indented multi-line formatting that adds whitespace without content.

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?

For a zero-parameter read-only diagnostic with no output schema, the description covers what is returned (backend type, connection status, metrics) and the access precondition. Minor gaps would be the exact metrics returned and whether it is safe to call repeatedly, but nothing essential is missing.

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?

The tool takes zero parameters, so the baseline is 4; there is nothing in the schema for the description to clarify. The description correctly implies no inputs are needed.

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 and resource ('Check database backend status and configuration') and enumerates what is reported: backend type (SQLite or PostgreSQL), connection status, and key metrics. That distinguishes it from generic probes like health_check or kiln_health, though no sibling is named explicitly.

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?

Gives two concrete use cases: verifying a PostgreSQL migration and diagnosing connectivity issues. It stops short of naming alternatives (e.g., health_check, license_status) or stating when not to use it, but the context is clear enough to route correctly.

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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