engineering_query_analytics

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

The description gives some context about routing and JWT/tenant/company scope, but it does not disclose any behavioral details such as side effects, data mutation, or potential destructive outcomes. The annotations already indicate destructive=true, but the description adds little beyond that.

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 concise and free of unnecessary fluff. It directly states the action, routing context, and parameters without redundancy.

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 description lacks information about the output/return format, expected behavior, potential errors, or any example usage. While it names the action and parameters, an agent would have limited understanding of what invoking this tool actually accomplishes or what to expect in the response.

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?

The schema provides no descriptions, so the one-line explanations for 'message' and 'inputs' add basic meaning. However, the explanations are generic and do not specify expected formats, examples, or how the structured inputs should be constructed.

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 names a specific action (`query_analytics`) and uses a clear verb ('Run'), so it is not a tautology. However, it does not explain what the analytics query actually does or what kind of data it returns, leaving the purpose vague. It also does not distinguish itself from the many other analytics/query-related sibling tools.

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 provides no guidance on when to use this tool versus alternatives such as shopify_analytics_query, quickbooks reports, or other domain-agent actions. Mentioning the dispatcher and scope explains mechanics, not usage context.

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