get_stock_transfer_suggestions

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It lists the exact Shopline APIs called (all GETs, implying read-only), explains the underlying algorithm, discloses the 30-product limit to avoid rate limiting, and describes the return structure. It does not mention permissions or error scenarios, but for a read-only analytical tool this is reasonably transparent.

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 with labeled sections for purpose, API calls, and return structure. Each section provides useful information without excessive verbosity. The only slight redundancy is that the parameter logic appears in both the purpose and the schema, but this is acceptable.

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 of moderate complexity (multi-API calls, algorithm, rate-limit caveat), the description is quite complete. It explains input (optional threshold), output fields, and underlying data sources. With no output schema, the return structure is explicitly described. Missing details like error handling or explicit permission requirements are minor gaps.

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 already documents min_stock_diff with 100% coverage, including its default and meaning. The description adds value by embedding the parameter in the algorithmic logic ('差值 >= min_stock_diff') and clarifying its role in triggering suggestions, which reinforces the schema's description and provides behavioral context.

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 '自動產生' (auto-generate) and the resource '跨倉庫庫存調撥建議' (cross-warehouse stock transfer suggestions). It explains the specific logic (threshold-based transfer suggestions) and distinguishes itself from sibling tools like get_stock_by_warehouse or get_inventory_overview by focusing on actionable suggestions rather than raw stock views.

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 clearly outlines the use case: to generate transfer recommendations based on inter-warehouse stock differences. It does not explicitly name alternatives or exclusions, but the purpose is self-evident and the tool's unique value proposition is clear. The note about analyzing only the first 30 products also provides context for when this might be insufficient.

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