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AI Down: live AI service status

get_status

Read-only

Live status of an AI service (Claude, Claude Code, ChatGPT, Codex, Gemini, Cursor, GitHub Copilot, OpenRouter) from independent probes and user reports. Omit service to get all.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
serviceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

readOnlyHint=true already establishes the safe-read profile, lowering the bar. The description usefully discloses that results are 'live' and aggregated from independent probes and user reports, but says nothing about refresh frequency, caching, or reliability of those sources.

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?

Two sentences, front-loaded with the core purpose and ending with the actionable omit instruction. The long enumeration of services is somewhat redundant with the enum but remains readable and scannable.

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 single optional-parameter read tool with no output schema, the description covers selection behavior adequately. It does not describe what a status result looks like (e.g., operational/degraded/outage values), which is a gap given the absence of an output schema.

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 0%, so the description must carry parameter meaning. It re-lists the eight service values (duplicating the enum, no added value) but does add real semantics by explaining that omitting the parameter returns all services. It still omits format expectations like case handling or partial matching.

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 names the resource (live status of an AI service) and its data sources (independent probes and user reports), which is more specific than a tautology. It clearly conveys a read/query operation, though it never states an explicit verb like 'retrieve' and there are no siblings to differentiate from.

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?

'Omit service to get all' gives a concrete instruction for the default/aggregate case, which is useful. However there is no guidance on when to query a single service versus all, and the usage context is largely implied rather than stated.

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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