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 search, ranking, and personalization behavior, but does not mention return format, edge cases, or whether the operation is read-only. This is moderate transparency but leaves some gaps.

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 sentences, front-loaded with the core purpose. No redundant or irrelevant information. Every sentence contributes meaningful detail.

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?

Despite lacking an output schema and annotations, the description adequately covers what the tool does, when to use it, and key behavioral aspects. The missing return format is a minor gap, but the description is sufficient for an agent to select and invoke the tool correctly.

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 covers all 5 parameters with descriptions, so the baseline is 3. The description adds value by explaining the overall algorithm (ranks by reward value, personalizes with user balances) and how intent and category interact, providing context beyond the schema.

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 action and resource: 'Find the best cashback deals and rewards matching a shopping intent.' It also describes specific behaviors (searches by category, ranks by reward value, personalizes based on user balances) that distinguish it from sibling tools like browse_perks or compare_cashback.

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 an explicit usage context: 'Use this when a user wants to shop, eat, travel, or game and wants the best rewards.' This gives clear guidance on when to use the tool, though it does not explicitly mention alternatives or exclusions.

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