fast_ai

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 mentions the performance characteristic (~100ms) which is valuable context, but doesn't address other important behavioral aspects like rate limits, authentication requirements, error handling, or what kind of responses to expect. For an AI tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

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 each serve a clear purpose: the first states what the tool does, the second provides usage guidance. There's zero wasted language, and the most important information (fast AI responses) is front-loaded appropriately.

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 an AI response tool with no annotations and no output schema, the description is insufficiently complete. While it mentions speed and use case, it doesn't describe what format responses come in, whether there are content limitations, authentication requirements, or error conditions. The agent would need to guess about important behavioral aspects of this tool.

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 schema has 100% description coverage with the single parameter 'content' described as 'Quick question.' The tool description doesn't add any additional parameter semantics beyond what's already in the schema. With complete schema coverage, the baseline score of 3 is appropriate since the description doesn't need to compensate for schema gaps.

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: 'Ultra-fast AI response via Groq (~100ms)' specifies the action (AI response), technology (Groq), and performance characteristic. 'Use for quick questions' further clarifies the intended use case. However, it doesn't explicitly differentiate from sibling tools like 'openrouter_chat' or 'think' that might also provide AI responses.

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 quick questions,' indicating this tool is optimized for speed over complexity. This gives practical guidance on when to choose this tool. However, it doesn't explicitly mention when NOT to use it or name specific alternatives among the many sibling tools.

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