think

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'Auto-routes to best AI capabilities' which adds useful context about how the tool works internally. However, it doesn't disclose important behavioral traits like whether this is a read-only operation, potential rate limits, authentication requirements, or what format the reasoning output takes.

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 extremely concise with just two sentences that efficiently convey the tool's purpose and usage. Every word earns its place - the first sentence defines the tool's function, and the second provides clear usage guidance. No wasted words or redundant information.

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 reasoning tool with 2 parameters, 100% schema coverage, but no annotations and no output schema, the description is adequate but has gaps. It explains what the tool does and when to use it, but doesn't address behavioral aspects like whether this is a safe operation, what the output format will be, or any limitations. The description compensates somewhat with the 'auto-routes' insight.

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%, so the schema already fully documents both parameters. The description doesn't add any additional meaning about parameters beyond what's in the schema. It mentions 'deep reasoning' and 'complex analysis' which relates to the query parameter's purpose, but provides no specific guidance on parameter usage or formatting.

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 purpose as 'Deep reasoning using cognitive orchestrator' with specific use cases like 'complex analysis, multi-step reasoning, research questions.' It distinguishes from siblings by focusing on cognitive processing rather than API key management, code execution, or data queries. However, it doesn't explicitly contrast with similar reasoning tools like 'consensus' or 'fast_ai'.

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 clear usage context with 'Use for complex analysis, multi-step reasoning, research questions,' giving specific scenarios when this tool is appropriate. It implies this is for more complex tasks than basic queries. However, it doesn't explicitly state when NOT to use it or name alternative tools for simpler reasoning tasks.

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