test_shopify_connection

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

No annotations are provided, so the description carries the full burden. It discloses that the tool validates credentials and OAuth permissions and uses stored config if needed. However, it does not explicitly state whether the operation is read-only or if it has side effects, nor does it describe what happens on success or failure. The behavioral disclosure is adequate but incomplete.

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 extremely concise, consisting of two short sentences and a tag. Every sentence provides essential information: the action, what is validated, and the fallback behavior. There is no redundancy or unnecessary detail, making it efficient for an AI agent to parse.

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?

The tool has no output schema, so the description should ideally hint at what the tool returns (e.g., success/failure status). It currently does not mention return values, which is a gap. Additionally, given the context of many sibling tools, it could clarify that this is a safe testing operation. The description covers the core functionality but lacks completeness regarding outcomes.

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?

Input schema has 100% description coverage for all 4 parameters, each clearly described. The description adds value by explaining the behavior when parameters are omitted (fallback to stored credentials), which enhances understanding beyond the schema alone. However, it does not add new semantic distinctions for each parameter, so a score 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?

The description clearly states the verb 'Probar' (test) and the resource 'conexion Shopify', and explicitly mentions validating credentials and OAuth permissions. It distinguishes this tool from sibling tools like test_ecommerce_connection by specifying Shopify, making its purpose 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?

The description implies when to use the tool (to test a Shopify connection) and notes that it can fall back to stored credentials. However, it does not specify when not to use it or suggest alternative tools like test_ecommerce_connection for other e-commerce platforms. Usage guidance is implied but not explicit.

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