learn_cloudcart_storefront

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 that a signed-in buyer is passed as an argument or @inContext(buyer:), never an Authorization header, that checkout belongs to the store (cart.checkoutUrl), that the server owns prices and money is rendered as `formatted`, and that carts use an unguessable key. It also warns that skipping it produces silently wrong totals. It omits repeat-invocation semantics and the exact shape of the returned guidance.

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 imperative call-to-action is front-loaded in the first line, followed by the payoffs in a compact enumerated form. The closing line ('the difference between a storefront that works and one that charges the wrong total') is rhetorical flourish rather than new information, though it does reinforce the stakes.

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 annotations and no output schema, the description must explain both what comes back and why it matters, and it does: the conversationId plus four concrete API-behavior facts an agent would otherwise get wrong. It stops short of describing the full contents of the returned guidance or flagging whether `model` is expected on first call.

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 both parameters are documented in the schema and the baseline is 3. The description reinforces the conversationId's significance (required by every other tool) but never mentions the `model` parameter or how conversationId should be echoed back on later calls.

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 the two outputs concretely: a conversationId required by every other tool, plus API knowledge the CloudCart schema omits (buyer auth, checkoutUrl, server-owned pricing, cart key). It never states the purpose in a single crisp sentence (e.g. 'loads the Storefront API usage guide'), and it does not name the sibling tools it precedes, but the effect is unambiguous.

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?

'Call this first, before anything else in this server' is an explicit ordering rule, and the schema covers the resume case ('Omit to start a new one'). It does not state when the tool can be skipped (already having a valid conversationId for the current session) or whether re-calling is wasteful, so there is no explicit when-not guidance.

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