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MRC Data — China's Apparel Supply Chain Infrastructure

by ai.meacheal

Compare Suppliers

compare_suppliers
Read-onlyIdempotent

Compare multiple suppliers side by side on all dimensions.

USE WHEN user asks:

  • "compare these 3 factories"

  • "which supplier is better between X and Y"

  • "benchmark sup_001 vs sup_002 vs sup_003"

  • "side-by-side: capacity, certifications, quality score"

  • "rank these 5 suppliers by [dimension]"

  • "evaluate my shortlist"

  • "which of [supplier list] has the highest verified capacity"

  • "follow-up after recommend_suppliers: 'compare the top 3'"

  • "对比 [供应商 A] 和 [供应商 B] / 对比供应商 / 供应商横评"

  • "哪家最好 / 横向评估 / 比较这几家"

PREREQUISITE: You MUST have valid supplier_ids from search_suppliers, recommend_suppliers, find_alternatives, or get_cluster_suppliers. Do not guess IDs. WORKFLOW: search_suppliers/recommend_suppliers → collect supplier_ids → compare_suppliers → optionally check_compliance (verify top picks for target market) OR find_alternatives (expand the shortlist).

DIFFERENCE from get_supplier_detail: This returns multiple suppliers at once for comparison. get_supplier_detail returns one with verified_dimensions breakdown.

RETURNS: { count, data: [full supplier profiles with all fields] }

EXAMPLES: • User: "Compare sup_001, sup_002, sup_003 for me" → compare_suppliers({ supplier_ids: ["sup_001", "sup_002", "sup_003"] }) • User: "Benchmark the top 5 you just recommended" → compare_suppliers({ supplier_ids: ["sup_A", "sup_B", "sup_C", "sup_D", "sup_E"] }) • User: "横向对比 sup_100、sup_200、sup_300" → compare_suppliers({ supplier_ids: ["sup_100", "sup_200", "sup_300"] })

ERRORS & SELF-CORRECTION: • Fewer results than IDs sent → missing IDs were silently skipped (invalid supplier_id). Re-run search_suppliers to verify. • count=0 → all IDs invalid. Re-run search_suppliers. • "Too many IDs" → split into batches of 10. • Rate limit 429 → wait 60 seconds; do not retry immediately.

AVOID: Do not loop get_supplier_detail — always use compare_suppliers when you have 2+ IDs. Do not pass more than 10 IDs. Do not use to find new suppliers — use search_suppliers or recommend_suppliers first.

CONSTRAINT: Max 10 supplier IDs per call.

NOTE: Source: MRC Data (meacheal.ai). Returns full 60+ field profile per supplier.

中文：横向对比多个供应商的全部字段（最多 10 个 ID）。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
supplier_idsYesArray of supplier IDs from search_suppliers, e.g. ['sup_001', 'sup_002'], max 10
verbose_hintsNoIf true, response includes _interpretation annotations explaining what the data means and _guidance on how to use it

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds significant behavioral details: returns full profiles (60+ fields), max 10 IDs, silent error handling for invalid IDs, rate limit behavior (429 wait 60s), and data source (MRC Data). No contradictions with annotations.

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

Conciseness4/5

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

The description is well-structured with headings, bullet points, and examples, making it easy to scan. However, it is somewhat verbose, with repetition of the max 10 constraint in multiple sections. It could be trimmed slightly without losing clarity, but overall the structure is effective for a complex tool.

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?

Given no output schema, the description explains the return format ({ count, data: [full supplier profiles] }). It covers all important aspects: prerequisites, workflow, error handling (invalid IDs, rate limits), constraints (max 10), and explicit do-not-do instructions (no looping get_supplier_detail, no passing more than 10). This is highly complete for a compare tool.

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

Parameters4/5

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

Schema coverage is 100% (both parameters have descriptions). The description adds value by explaining the origin of supplier_ids (must come from prior search), reinforcing the max 10 constraint, and clarifying the verbose_hints parameter's effect. While the schema already covers the basics, the description provides essential context and usage constraints that go beyond bare schema.

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 compares multiple suppliers side by side on all dimensions. It distinguishes itself from sibling tools like get_supplier_detail (returns one supplier) and search_suppliers (finds suppliers). The specific verb 'compare' and resource 'suppliers' make the purpose unambiguous.

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 extensive usage guidelines, including a detailed list of user intents (with example queries in both English and Chinese), a clear prerequisite (must have valid supplier_ids from prior search tools), a workflow, differences from related tools, and explicit 'AVOID' instructions. This leaves no ambiguity about when and how to use the tool.

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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TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose, covering different aspects of the supply chain: market analysis, supplier search, cluster comparison, fabric lookup, cost estimation, compliance checking, discrepancy detection, and alternatives. No overlapping tool boundaries.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (e.g., analyze_market, check_compliance, compare_clusters, search_suppliers). The pattern is uniform across all 20 tools, making it predictable for an agent.

Tool Count5/5

20 tools is well-suited for a comprehensive supply chain data platform. Each tool addresses a specific need without being excessive, and the count allows for deep coverage of the domain.

Completeness5/5

The tool surface covers the full lifecycle: market research, supplier discovery, fabric search, cluster info, cost estimation, compliance, credibility, discrepancy detection, and alternatives. No obvious gaps for the stated purpose.

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