Pricing Analysis

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds valuable context about the exact output structure (array of product data with specific fields) and the nature of the analysis, which goes beyond what annotations provide. No contradictions found.

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, using only two sentences. The first sentence clearly states the tool's core function, and the second provides essential details about output and parameter usage. No redundant or irrelevant information is present.

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's complexity (2 parameters, no output schema), the description covers the output structure thoroughly, compensating for the missing output schema. It explains parameter scoping but does not mention potential pagination, error handling, or sorting order. Still, it is largely sufficient for an analysis tool with clear annotations.

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, so parameters are already documented. The description adds value by explaining that omitting product_id analyzes the full catalog and by detailing the output fields that relate to the parameters (e.g., suggested_price for product). This clarifies the effect of parameter choices beyond schema constraints.

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 ('Analyze pricing') and resource ('products'), and clearly lists the key metrics (margin, sales velocity, optimization suggestions). It differentiates from the sibling 'pricing_optimize' by focusing on analysis rather than application of changes.

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 explains when to include or omit product_id for scoping, which is useful. However, it does not explicitly state when to use this tool versus the sibling 'pricing_optimize', leaving the agent to infer the distinction. No when-not-to-use or alternative guidance is provided.

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