intelligence-api

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

No annotations are provided, so the description carries full disclosure burden. It lists what data is extracted but omits safety profile (read-only vs. destructive), authentication requirements, rate limiting, caching behavior, or what happens with invalid/non-Shopify URLs.

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?

Highly efficient single-sentence structure. The em-dash enumeration of analysis targets delivers maximum information density with zero redundancy. Every element (products, pricing, apps, theme) earns its place in defining scope.

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?

Despite lacking an output schema, the description effectively documents return value categories (pricing distribution, detected apps, etc.), giving agents clear expectations of analysis depth. Minor gap regarding error handling or edge cases prevents a 5.

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?

With 100% schema description coverage for the single 'url' parameter, the baseline is 3. The description adds minimal semantic value beyond the schema, mentioning 'any Shopify store' but not adding format constraints, validation rules, or protocol requirements beyond the schema's example.

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 analyzes Shopify stores with specific capabilities enumerated (products, pricing distribution, vendors, detected apps with examples, theme, collections). It effectively distinguishes from sibling 'shopify_products' by emphasizing comprehensive store analysis versus simple product listing.

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?

While the scope (comprehensive analysis vs. simple product retrieval) implicitly differentiates it from 'shopify_products', there are no explicit guidelines on when to prefer this tool over alternatives, prerequisites like store accessibility, or error conditions.

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