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

With no annotations, the description carries the full burden and does most of it: it discloses that only connected sources appear, and that in multi-store mode the store param filters only Shopify data while GA4/Klaviyo/Search Console/Gorgias stay account-level and always aggregated. It does not cover auth requirements, rate limits, or the concrete return shape beyond 'lean snapshot'.

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?

Front-loaded with the capability, then the drill-down guidance, then the multi-store caveats. Dense and mostly waste-free, though the final multi-store/store-comparison sentences are long enough that some tightening is possible.

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?

No output schema and no annotations, so the description must supply context, and it does: scope, trigger scenarios, cross-source aggregation behavior, and store-filtering limits. What is missing is return-shape detail (what fields a snapshot contains, pagination interaction with _offset).

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 startDate/endDate/_offset semantics are already documented, making 3 the baseline. The description adds useful behavioral detail about the store param's partial filtering, but that parameter does not appear in the input schema, so the added semantics do not map cleanly onto any documented parameter.

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?

States a specific verb+resource ('Get a unified dashboard') and enumerates the metric domains covered (revenue, traffic, marketing, email, organic search, UX, support, reviews, subscriptions, loyalty), which clearly separates it from the many single-domain siblings like get_marketing_performance or get_product_analytics.

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 names the trigger phrases ('Give me an overview', 'How is the business doing?') and routes the agent onward ('then drill into specifics with individual tools'). It also names the alternative for a related need, get_store_comparison, and notes the condition under which that tool exists.

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