shopify_list_stores

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

Annotations already indicate readOnlyHint=true and openWorldHint=true, so the description's extra detail about the cached `name` field and the `refresh` bypass behavior adds meaningful transparency. The description also discloses that data is fetched once per process and cached, which helps the agent understand freshness semantics beyond what annotations convey.

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 well-structured and front-loaded: it states the core purpose in the first sentence, then the return shape, usage guidance, and a single clearly documented parameter. Every sentence earns its place, and the Args section is minimal and scannable.

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 simple read-only listing tool with one optional parameter, the description is complete: it specifies the return fields, the caching behavior, the refresh condition, and the mapping use case. The output schema also exists, so the description does not need to over-explain return types, and no critical invocation detail 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?

Although schema description coverage is 0%, the description fully documents the single `refresh` parameter: 'If True, bypass the shop-name cache and re-fetch from Shopify' and explains when to use it. This compensates for the missing schema description and gives the agent actionable semantics.

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 opens with a specific verb and resource: 'List all Shopify stores configured for this agent.' It clearly explains the return shape and also gives a concrete use case, distinguishing this tool from the GraphQL and bulk-query siblings by emphasizing it returns the agent's configured store list, not API queries.

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 clear context for when to use the tool: to match user intent to a configured store, including a concrete example. It also provides the conditional guidance that if only one store is configured, `shop` can be omitted. It does not explicitly exclude alternatives, but the usage context is clear enough.

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