openai_query

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that the tool makes a direct call to OpenAI, uses GPT-4o by default, and bypasses AION's persona and memory—an important behavioral distinction. However, it does not mention potential costs, rate limits, or what the response contains, but for a simple query tool this is reasonably transparent.

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?

The description is two concise sentences: the first states the core action and default behavior, the second provides usage guidance. No fluff, and it is front-loaded with the most critical information. Excellent structure for an AI agent.

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?

For a tool with no output schema and no annotations, the description covers the essential facts: what it does, the default model, and when to use it. It omits return-value details and cost implications, but these are secondary for a straightforward query tool. Overall, it is adequately complete for the tool's simplicity.

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?

Schema description coverage is 100%, with all four parameters (prompt, model, system, temperature) already described in the schema. The description adds no additional parameter semantics beyond the schema; it only reiterates the default model. Since the schema is fully self-explanatory, the baseline score of 3 is appropriate.

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 description clearly states the tool's function: 'Send a raw prompt directly to OpenAI (GPT-4o by default)'. It uses a specific verb ('send') and resource ('prompt to OpenAI'), and distinguishes from siblings by noting it bypasses AION's persona and memory, which differentiates it from aion_query and other AION-context tools.

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?

The description provides explicit usage scenarios: 'Useful for one-off queries, comparing model outputs, or when Ollama is unavailable.' It gives clear context for when to use the tool but does not explicitly name an alternative tool like aion_query, though the 'bypassing AION' phrase implies when not to use it. This is strong but not fully explicit about alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.