Trustbase Lab · rCB & Chemical Recycling Data

List Verified Suppliers

get_verified_suppliers

Read-onlyIdempotent

Purpose: return every company/project carrying verified=true (A-grade confidence, backed by government filingsor official announcements) - the trust layer an agent should use when shortlisting counterparties. Guidelines:call this first for any recommendation, shortlisting or transaction-style task; pair with get_company for fulldetail on the chosen entity; use language='en' plus response_format='json' for downstream automation. Limits:A-grade records only - absence from this list does not mean a company is untrustworthy, only that its claim isnot yet independently verifiable; at most 100 rows; no commercial rating, ranking or endorsement is implied. Ex:get_verified_suppliers(), get_verified_suppliers(limit=100, language='en', response_format='json').

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	返回条数上限（默认 50，最大 100）
`language`	No	输出语言：zh=中文（默认）, en=英文	zh
`response_format`	No	输出格式：markdown=人类阅读（默认）, json=Agent 处理友好	markdown

Output Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes	Human-readable result (markdown, or a JSON string when response_format=json).

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 20, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "text": {
+      "description": "Human-readable result (markdown, or a JSON string when response_format=json).",
+      "type": "string"
+    }
+  },
+  "required": [
+    "text"
+  ],
+  "type": "object"
+}

First observedSep 15, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=false. The description adds useful context: the limit of 100 rows, the interpretation of absence (not untrustworthy), and the lack of commercial rating/ranking. This goes beyond the safety profile to clarify data semantics.

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 structured paragraph with clear sections (Purpose, Guidelines, Limits, Ex) and front-loads the core purpose. It is dense but every sentence serves a purpose; a minor issue is that it could be slightly shorter, but the structure aids readability.

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 that an output schema exists (so return values are separately documented), the description fully covers purpose, usage, limits, and parameter guidance. Nothing an agent needs to know in order to call this tool correctly is missing.

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% and all parameters have descriptions. The description adds value by recommending specific parameter combinations (language='en' + response_format='json') for downstream automation and demonstrating usage in examples, which the schema alone doesn't convey.

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 it returns companies/projects with verified=true, and explains the 'trust layer' context. It distinguishes itself from siblings by specifying 'call this first' and pairing with get_company for detail, making its scope 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 explicitly instructs when to use this tool ('call this first for any recommendation, shortlisting or transaction-style task'), how to pair it with get_company, and provides parameter usage guidance for automation (language='en', response_format='json'). Examples reinforce the intended invocation pattern.

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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