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

No annotations are provided, so the description must handle transparency fully. It mentions using historical prices and trends but does not disclose if the tool is read-only, any rate limits, or what the output looks like. More detail on behavior would be beneficial.

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 two sentences plus a note. It is front-loaded with the core purpose and use cases, and every sentence adds value without 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 the tool has only one parameter and no output schema, the description covers purpose, usage, and parameter source. However, it does not describe the return format or any failure modes, which would improve completeness for a tool that produces a decision.

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 has 100% description coverage for the single parameter (offer_id). The description additionally explains where to obtain the offer_id, providing context beyond the schema. This warrants a score above baseline.

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: to determine if a product is a good buy now using historical prices and trends. It provides specific example user queries (e.g., 'Should I buy XX now?', 'Is this price good?') and distinguishes itself from siblings by focusing on the buy/wait decision.

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 specifies when to use the tool (when users ask about buying decisions) and explains how to obtain the required parameter (offer_id from search_products/compare_prices). It does not explicitly state when not to use it, but the context is clear.

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