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get_china_supplier_evidence_full

Paid $0.01 USDC on Base via x402: full Chinese supplier due diligence with detailed evidence rows, dataset coverage, procurement awards, regulatory history, provenance and ambiguity-safe linkage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.7/5.0
Behavior3/5

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

With no annotations, the description must carry behavioral context. It usefully discloses a concrete behavioral trait: 'Paid $0.01 USDC on Base via x402'. It also lists output categories like procurement awards and regulatory history. However, it does not explain failure modes, response shape, or what happens when no evidence is found.

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 a single, dense sentence that packs payment, scope, and output categories without padding. The payment requirement is front-loaded, and the list of evidence types earns its place, though the run-on structure is slightly hard to parse.

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

Completeness2/5

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

Given the nested request schema, payment requirement, and sibling tools, the description leaves several gaps: it never explains how evidence_limit or include_evidence affect behavior, how to provide the company/USCC, or what 'ambiguity-safe linkage' means operationally. It names important output categories but not enough context for confident invocation.

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

Parameters1/5

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

Schema description coverage is 0%, and the description provides no meaning for the request parameters, USCC, company, evidence_limit, or include_evidence. It mentions data categories but does not connect them to any parameter, so it does not compensate for the low coverage.

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

Purpose4/5

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

The description identifies a clear resource ('full Chinese supplier due diligence') and distinguishes it from the sibling 'basic' tool via 'full' and 'detailed evidence rows'. However, it opens with a payment phrase rather than a direct verb+resource statement, slightly reducing clarity.

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

Usage Guidelines2/5

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

No guidance is given on when to use this tool instead of get_china_supplier_evidence_basic or resolve_china_company. The description implies a fuller result set, but it never states selection criteria, exclusions, or alternatives.

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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