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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real behavior beyond that: this executes the actual production mapping pipeline (not a mock) and the output includes overrides and market prices, which is meaningful context an agent could not infer from the 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 tight sentences with zero filler; the high-value scope and return-content information is front-loaded before the usage hint.

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?

An output schema exists, so return values needn't be enumerated, and the description still characterizes the payload (exact Google items, overrides, market prices). The only minor gap is variant pagination behavior, which the schema already covers via the page parameter.

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 100% – feedId, productId, and page are all documented in the schema, including pagination size and defaults. The description adds no additional parameter meaning, so baseline 3 applies.

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?

States a concrete verb+resource: it runs the real feed mapping pipeline for one product and returns the exact items Google would receive. The emphasis on 'ONE product' implicitly separates it from the feed-wide run_feed sibling, but it never names an alternative, leaving the differentiation to inference.

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?

Gives a clear situational trigger: 'Use after edits to verify the output.' That tells the agent when to reach for it, but there is no explicit when-not guidance and no named alternative (e.g., use run_feed for a full-feed validation).

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