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

No annotations are provided, so the description carries the full behavioral burden. It adds useful context about sources and currency units, but it does not disclose return shape, time-series granularity, permissions, or other behavioral details needed to invoke confidently.

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 short sentences with the key concept front-loaded. Every sentence contributes: the first identifies the data and sources, and the second clarifies the unit.

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?

With no output schema and no annotations, the description is too sparse for a historical pricing tool. It clarifies sources and units but does not explain what a pricing snapshot contains, how days/condition affect results, or what the response looks like.

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 description coverage is high at 80%, so the schema already documents most parameters including days, source, product_id, and notification_message. The description adds source and unit context but does not add parameter-level meaning beyond the schema, so the baseline of 3 is appropriate.

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 states a clear resource (historical pricing snapshots) and sources (Cardpeer and market), so the tool is distinguishable from product/catalog/search siblings. It does not explicitly contrast itself with search_listings or get_product, but the pricing focus is clear.

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 gives no explicit when-to-use guidance, no prerequisites, and no indication of when an agent should call get_pricing instead of get_product or search_listings. Historical pricing is implied by the purpose, but there is no actionable routing guidance.

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