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Test an OptiQra AI provider key

optiqra_ai_test

Verify that a specified AI provider, API key, and model combination is reachable and working, ensuring readiness for AI-driven fixes and insights.

Instructions

Verifies that a given AI provider + API key + model combination is reachable and working, before using optiqra_ai_fix or optiqra_ai_insights.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoOptional specific model name to test.
apiKeyNoAPI key for the chosen provider. Optional if OPTIQRA_PROVIDER_API_KEY is set in this server's environment.
providerYesAI provider to use for this request.
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It only states the verification intent but omits any side effects, whether the operation is read-only, the meaning of 'working', or the response format. For a tool that likely performs network calls, this leaves important behavioral traits undisclosed.

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 a single, front-loaded sentence that immediately states the action and context. It contains zero filler or redundancy, making it highly efficient.

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 relatively simple verification tool, the description is adequate but incomplete. It lacks any mention of success/failure outcomes, whether the call is destructive, or how the result is returned. Given no output schema and no annotations, more detail would be valuable for the agent to set expectations.

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?

The input schema has 100% description coverage, so the parameters are already well documented. The description adds minimal semantic value beyond listing the combination in prose; it does not introduce dependencies, constraints, or environment-specific details beyond what the schema already includes for apiKey.

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 a specific verb 'verifies' with a clear resource ('AI provider + API key + model combination') and explicitly distinguishes the tool's role from the sibling tools by naming optiqra_ai_fix and optiqra_ai_insights. This makes the purpose unmistakable and contextually differentiated.

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 states to use this tool 'before using optiqra_ai_fix or optiqra_ai_insights', providing clear timing guidance. It does not mention when to avoid using it or alternatives beyond the implied sequencing, but the primary usage context is well conveyed.

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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