Skip to main content
Glama

get_system_status

Read-only

Check system health by verifying database connectivity, pipeline queue depth, and per-source crawl status to diagnose data ingestion issues.

Instructions

Get system health status including database connectivity, pipeline queue depth, and per-source crawl health.

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": "get_system_status"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds what areas are reported, which is real added context. However, it says nothing about freshness/snapshot semantics despite idempotentHint=false (results change over time), nor about latency, rate limits, or failure signalling - all relevant for a health-check 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?

A single front-loaded sentence that names the resource first and then the concrete contents. Zero filler and nothing redundant.

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 status probe with no output schema, the description is nearly sufficient: it tells the agent what categories of information come back. It only lacks a note on snapshot/freshness semantics or what an unhealthy result looks like, which would have made it complete.

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 schema has nothing to document and the baseline of 4 applies. The description correctly implies the call is argument-free and scope-free.

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 ('Get system health status') and enumerates the three reported areas: database connectivity, pipeline queue depth, per-source crawl health. That is far more specific than the name alone. It does not explicitly differentiate from siblings, but no sibling overlaps this diagnostic surface, so the omission is minor.

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?

Usage is only implied: an agent can infer this is the tool for checking whether the platform is healthy before or after running data queries. There is no explicit 'use this when...' framing, no mention of when not to use it, and no named alternative (none of the siblings are substitutes).

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