get_ai_service_availability
Which AI services (ChatGPT, Claude, Gemini, HuggingFace, …) are reachable per country — state blocking vs vendor geo-restriction, labeled separately.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Which AI services (ChatGPT, Claude, Gemini, HuggingFace, …) are reachable per country — state blocking vs vendor geo-restriction, labeled separately.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful semantics by stating that state blocking and vendor geo-restriction are labeled separately in the results, but it says nothing about freshness, coverage scope, or how the labels appear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no filler: the scope (per country), the resource (AI services), and the distinguishing output semantics are all packed into one clause with zero waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no parameters and no output schema, the description carries the burden and mostly meets it by stating what is returned conceptually (per-country reachability with separately labeled blocking types). A brief note on data source or freshness would close the remaining gap, but nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so the baseline of 4 applies; there are no parameter semantics for the description to clarify or omit.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The one-liner names a concrete resource (AI services such as ChatGPT, Claude, Gemini, HuggingFace) and the scope (per country), and adds the key distinction between state blocking and vendor geo-restriction. It does not explicitly name the closest siblings (check_service_accessibility, check_domain_blocked), so an agent must infer the routing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no when-to-use, when-not-to-use, or alternative naming, despite heavy overlap with check_service_accessibility and check_domain_blocked in the sibling list. Usage is only implied by the topic itself, which is insufficient for choosing among several similar availability tools.
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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