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 data freshness ('checked every 6 hours'), an explicit exclusion ('second-hand stock is excluded'), and the shape of the result (lowest new in-stock UK price today, retailer count, buy/wait verdict, link to history). It omits auth/permission needs and any rate-limit or pagination behavior, which keeps it short of a 5.

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 the action and scope, then return values, then freshness and exclusion caveats. No filler, no repetition of the title, and each clause adds information an agent needs.

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 compensates well by enumerating what comes back and how fresh the data is. It is slightly incomplete on the meaning of the 'buy/wait verdict' and on result-volume behavior beyond the schema's limit field, but nothing essential for a correct call 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?

Schema description coverage is 100%, so the schema already documents all four parameters, including query and category examples. The description's examples ('Pro V1', 'TaylorMade driver', 'rangefinder under 200') largely restate the schema and only mildly illustrate how query interacts with max_price, 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?

States a specific verb and resource ('Search ... live UK golf price tracking by model, brand or category') with concrete query examples, and the plural framing ('each matching model's lowest ... price') functionally separates it from the single-price get_golf_price and the drop-oriented golf_price_drops. An agent can tell what this tool does without opening the schema.

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 useful input-side guidance (what can be searched, example queries, a price-filter example) and scope limits (UK, new stock only), but never says when to use this versus get_golf_price or golf_price_drops. Routing among the three siblings is left entirely to inference.

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