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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value beyond annotations by specifying that the tool never raises protocol errors but returns {'error': ...} and explains the safety of retrying after correction. It also provides a concrete example of the output structure, which is not in the annotations.

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 with the core purpose, followed by an example, usage guidelines, error handling, and retry note. While slightly verbose, every sentence provides useful information—no fluff. It is organized clearly and easy to scan.

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 tool with 2 simple parameters (one required), an output schema, and clear annotations, the description covers all necessary details: purpose, usage context, parameter examples, error handling, and behavior. It is complete for an agent to invoke correctly without additional clarification.

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% for both parameters (header_row and mode). The description adds value with a concrete input example and clarifies the mode semantics ('new' vs 'update') via the schema, but the description itself also reinforces the meaning and error conditions. The example demonstrates the expected parameter format and output, which goes beyond the schema.

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 tool's purpose: to check a product CSV's header row against Shopify's current columns. It specifies the exact resource (header row) and the type of check (against Shopify's current columns), and it is distinct from siblings like url_handle (checks a handle) and metafield_key_check (checks a metafield key). The example and error handling reinforce the purpose.

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 when to use ('Use before an import, on the header row alone') and when not to ('Not for whether the values in the rows are valid'), and points to alternatives (url_handle, metafield_key_check). Also provides retry guidance. This is unambiguous and actionable.

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