get_price_suggestion

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

With no annotations, the description carries the full burden and does well: it discloses the real gotcha that not every listing has a suggestion due to insufficient data, that partial data is returned as-is, and it enumerates the returned fields. It omits auth/permission requirements and any rate-limit behavior, keeping it out of 5 territory.

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?

Three sentences, front-loaded with purpose, followed by usage and a clearly labeled 'Gotcha'. Every sentence carries information the agent needs; nothing is padding.

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?

For a single-parameter read tool with no output schema, the description is complete: it covers purpose, triggering scenarios, the failure mode (partial/absent suggestion), and the shape of the return. Nothing an agent needs in order to call it correctly is missing.

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?

Only one parameter with 100% schema coverage, so the schema already documents item_id and its site-prefix format. The description adds no format or syntax detail beyond that, matching the baseline-3 rule.

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?

Names a specific verb+resource ('Get Mercado Livre's competitive price suggestion') and pins the scope to 'one of your listings' with the basis (comparable sales). An agent can distinguish this from get_listing_prices, the raw-price sibling, because the description frames it as a recommendation rather than a price read.

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?

Explicitly states the triggering user intents — 'whether a listing is priced right' or 'wants to undercut the competition' — which is clear usage context. It does not name an alternative tool or a when-not-to-use condition, so it stops short of a 5.

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