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is_service_down

Read-onlyIdempotent

Check whether a named AI service (e.g., Claude, OpenAI) is operational, degraded, or down, with component-level breakdown. Use before sending traffic to avoid failures.

Instructions

Check whether one named AI service (e.g. "claude", "openai", "gemini", "mistral", "cohere", "hugging face", "replicate") is currently operational, degraded, or down, with its component-level breakdown. Matches on service or provider name and lists available services if there is no match, so an agent can gate a call on live status before sending traffic. Free, no auth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
serviceYesService name to check (e.g. "claude", "openai", "gemini", "mistral", "cohere", "hugging face", "replicate")
Behavior4/5

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

Annotations already indicate read-only, idempotent, and open-world behavior. The description adds context about how matching works, including listing available services on no match and providing component-level breakdown. No contradictions with annotations.

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?

Three sentences, front-loaded with purpose. Each sentence is useful: purpose, matching behavior, usage guidance, and free/no auth. Could be slightly tighter but effective.

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 simple health-check tool with one parameter and no output schema, the description covers purpose, behavior, and usage context. Missing details on response format are minor given the tool's simplicity.

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?

Schema covers the parameter with examples. The description goes beyond by explaining matching behavior and what happens if no match is found, adding value over schema alone.

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 the tool checks the operational status of named AI services, listing examples like 'claude' and 'openai'. It also mentions matching behavior and listing available services on no match, which distinguishes it from siblings like 'get_ai_status'.

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 explicitly says 'so an agent can gate a call on live status before sending traffic', providing a clear use case. It also notes the tool is free and requires no auth, aids in decision-making. However, it does not explicitly state when not to use or mention alternatives.

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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