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Search Suppliers

search_suppliers
Read-onlyIdempotent

Find verified Chinese apparel manufacturers and clothing suppliers by filtering location, production capacity, product type, and compliance status to match specific sourcing requirements.

Instructions

Search verified Chinese apparel manufacturers, apparel factories, and clothing suppliers.

USE WHEN user asks:

  • "find me a clothing manufacturer in China / Guangdong / Zhejiang"

  • "who makes [t-shirts / suits / denim / activewear] in China"

  • "I need a BSCI / OEKO-TEX certified apparel factory"

  • "looking for OEM / ODM apparel supplier with MOQ < N"

  • "find factories with production capacity > N pieces/month"

  • "搜供应商 / 找服装厂 / 找制衣厂"

Filters: province, city, factory type (factory/trading_company/workshop), product category, minimum monthly capacity, compliance status, quality score. Returns paginated supplier list with company name, location, monthly capacity (lab-verified), compliance, quality score.

WORKFLOW: This is the primary entry point for supplier discovery. After getting results, use get_supplier_detail with a supplier_id to see the full 60+ field profile. RETURNS: { has_more: boolean, available_dimensions: string[], data: [{ supplier_id, company_name_cn, company_name_en, type, province, city, product_types, quality_score, verified_dims: "5/8", coverage_pct }] } ERRORS: Returns empty data array if no matches. Max 50 results per page. FALLBACK: If no results, try broadening: remove city (keep province), remove product_type, or lower min_capacity. Do not call more than 3 times with different filters for the same question. NOTE: Use this for FILTERING by exact criteria. For ranked recommendations based on sourcing needs, use recommend_suppliers instead.

中文:搜索经过核查的中国服装供应商档案,按地区、类型、产能、品类、合规状态等筛选。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoSearch by company name — Chinese (广州新鑫) or English (Xinxin Garments)
provinceNoProvince in China (e.g. 广东 Guangdong, 浙江 Zhejiang, 江苏 Jiangsu, 福建 Fujian, 山东 Shandong)
cityNoCity name
typeNoSupplier type
product_typeNoProduct category keyword (e.g. 西装 suits, 女装 womenswear, 牛仔 denim, 运动服 activewear, t-shirt, 衬衫 shirts)
min_capacityNoMinimum monthly production capacity (pieces)
compliance_statusNoCompliance status filter: compliant / partially_compliant / non_compliant
data_confidenceNoData quality filter: verified / partially_verified / unverified
min_quality_scoreNoMinimum quality score 1-10
limitNoPage size: number of records to return (1-50, default 10)
offsetNoPagination offset: skip this many records before returning results (default 0)
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering safety profile. The description adds valuable behavioral context beyond annotations: pagination details (max 50 results per page, returns empty array if no matches), fallback strategies, usage limits (max 3 calls), and clarifies it's for filtering by exact criteria rather than recommendations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (USE WHEN, Filters, WORKFLOW, RETURNS, ERRORS, FALLBACK, NOTE) and every sentence adds value. It's appropriately sized for a complex tool with many parameters and workflow considerations, with no redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex search tool with 11 parameters and no output schema, the description provides comprehensive context: detailed return format specification, error behavior, pagination limits, workflow integration with get_supplier_detail, fallback strategies, and clear differentiation from sibling tools. It compensates well for the lack of output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the schema already fully documents all 11 parameters. The description lists available filters (province, city, factory type, etc.) but doesn't add syntax or format details beyond what the schema provides. The baseline of 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches for 'verified Chinese apparel manufacturers, apparel factories, and clothing suppliers' with specific resource scope. It distinguishes from siblings by explicitly naming 'recommend_suppliers' as an alternative for ranked recommendations, not filtering by exact criteria.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage scenarios with example user queries, clear workflow guidance (primary entry point for discovery, then use get_supplier_detail), and explicit alternatives (use recommend_suppliers for ranked recommendations). It also includes fallback strategies and usage limits (max 3 calls for same question).

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

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