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

Annotations already define read-only, open-world, and idempotent behavior. The description adds meaningful context: it returns full per-agent scoring data plus comparison context, and notably reveals that the tool does not declare a universal winner — showing evidence differences. This goes beyond the annotations and helps the agent interpret results.

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 compact and well-structured: purpose, return value, usage, and a critical behavioral caveat are each covered in a single short paragraph. No filler or redundant phrases; every sentence earns its place.

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?

Given the presence of an output schema and strong annotations, the description sufficiently covers the tool's function, return type, and usage. It could mention limitations or edge cases, but for a read-only comparison tool with sibling differentiation, it is quite complete.

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 input schema already documents 'handles' as 'Array of 2-5 agent handles to compare' (100% coverage). The description merely restates '2-5 AI agents' without adding new parameter-specific detail. Baseline 3 applies because the schema carries the semantic load.

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 uses a specific verb ('Compare') and resource ('AI agents'), and clarifies the scope ('across all their categories'). It also distinguishes from sibling tools like get_agent_details by framing it as side-by-side comparison, making the purpose unmistakable.

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?

Explicitly says 'Use for "X vs Y" queries', giving a clear when-to-use context. It also notes that no universal winner is declared, setting expectations for the output. However, it doesn't name alternative sibling tools or explicitly state when not to use it, so it stops short of a 5.

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