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

Annotations indicate a read-only operation, and the description adds significant behavioral detail: token-AND matching, a limited result set of up to 5 active deals, specific return fields, and a no_match block. No contradictions with annotations.

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?

Two sentences that are front-loaded with essential details: the core function and matching logic in the first, and important edge-case behavior in the second. No wasted words.

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 no output schema, the description covers all critical aspects: input query, matching, result fields (price, discount, condition, merchant, URL, human_summary), limit, and the no-match fallback. It is comprehensive for the tool's complexity.

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 coverage is 100%, and the description adds value by explaining the token-AND matching logic for the query parameter and the default limit of 5. It also clarifies the scope of matching fields, going beyond schema descriptions.

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 specifies a clear action: search live, human-reviewed deals by keyword. It details the matching method (token-AND over product name, brand, category, and merchant) and what is returned, making it distinct from sibling tools like get_deal or register_watch.

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?

It explains when to use (searching deals) and handles the zero-match case by directing to register_watch. However, it does not explicitly differentiate from other search-related siblings like latest_deals, leaving some ambiguity.

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