Get Fabric's Suppliers

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false, covering safety and idempotency. The description adds valuable behavioral context beyond annotations: it specifies sorting by quality score, details the return structure (including fields like quality_score, price_rmb, moq), and notes that it returns count=0 if no suppliers are linked. This enhances transparency without contradicting 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 with clear sections (purpose, usage examples, prerequisite, workflow, returns, errors, and a Chinese summary). It is front-loaded with the core purpose and avoids redundancy. However, the inclusion of both English and Chinese versions slightly reduces conciseness, though each sentence earns its place by adding value (e.g., error handling details).

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?

Given the tool's moderate complexity (one parameter, no output schema), the description is highly complete. It covers purpose, usage guidelines, prerequisites, workflow integration, return structure, and error conditions. With annotations providing safety and idempotency hints, and the description adding sorting behavior and output details, it leaves no significant gaps for an AI agent to understand and invoke the tool correctly.

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%, with the single parameter 'fabric_id' fully documented in the schema as 'Fabric ID from search_fabrics, e.g. FAB-W007'. The description reinforces this by mentioning the prerequisite of having a fabric_id from search_fabrics, but does not add significant semantic details beyond what the schema provides. Thus, it meets the baseline of 3 for high schema coverage.

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: 'List all suppliers offering a specific fabric, sorted by quality score, with price comparison.' It specifies the verb ('List'), resource ('suppliers'), and scope ('offering a specific fabric'), and distinguishes it from siblings like 'get_supplier_detail' or 'compare_suppliers' by focusing on fabric-specific supplier listings with quality-based sorting and price comparison.

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 explicit usage guidelines with 'USE WHEN' examples (e.g., user asks about suppliers for a fabric or price comparisons) and 'PREREQUISITE' (must have a valid fabric_id from search_fabrics). It also includes a 'WORKFLOW' section that outlines the sequence (search_fabrics → pick fabric_id → get_fabric_suppliers), clearly indicating when and how to use this tool versus alternatives.

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