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API Status Check

by io.github.shibley
OverviewDiscussionsAdmin

Check an API right now

get_api_status

Probe a monitored API endpoint at call time and return up/degraded/down with the response time. This is the tool to reach for when a user asks "is X down?" — it makes a real request rather than reading the hourly cache.

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": {
      "slug": "<slug>"
    },
    "name": "get_api_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugYesAPI slug, e.g. "openai". Use search_apis to resolve a name.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description must disclose behavior. It clearly states this tool performs a live probe at call time and returns a status plus response time, which is critical behavior beyond the schema. However, it does not mention potential side effects like latency or rate limiting, leaving minor gaps.

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, front-loaded with the core action and result, then immediately provides a practical usage example. Every word adds value with no waste or redundancy.

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?

For a simple, real-time probe tool with one parameter and no output schema, the description is complete: it explains the return values (up/degraded/down, response time), the live nature, and the use case. No important context 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% and the single parameter 'slug' is already well-described in the schema with an example and reference to search_apis. The description does not add parameter-level details, but the schema fully covers it, so the baseline of 3 is appropriate.

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 uses the specific verb 'probe' and clearly identifies the resource ('monitored API endpoint') and the action ('return up/degraded/down with the response time'). It explicitly distinguishes itself from sibling tools by contrasting with 'reading the hourly cache,' making the tool's purpose unambiguous.

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?

The description provides direct usage guidance: 'This is the tool to reach for when a user asks "is X down?"' and explicitly notes it 'makes a real request rather than reading the hourly cache,' which implies when not to use it (when a cached answer is acceptable). This effectively differentiates from sibling tools like list_down_apis.

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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