Trustbase Lab · rCB & Chemical Recycling Data

Search Industry Articles

query_articles

Read-onlyIdempotent

Purpose: search the first-hand research archive of the RCB industry WeChat official account - conferencecoverage, process cases, application boundaries and institution-level market forecasts. Guidelines: keywordmatches title/topic/author/scope; filter with category for a single theme; every item is A-grade (first-handresearch) and carries publish date, topic, source URL and AI-readable summary. Limits: Chinese-language sourcematerial; A-grade here means first-hand, not independently peer-reviewed; coverage is 63 articles from 2026-04onward, not the account's full history. Ex: query_articles(keyword='Pyrum'),query_articles(category='市场预测·机构观点'), query_articles(keyword='EPDM', language='en').

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	返回条数上限（默认 20，最大 100）
`keyword`	No	关键词模糊匹配（标题/主题/作者/适用范围），如 '曼谷'、'Pyrum'、'EPDM'、'预测'
`category`	No	主题分类过滤，如 '国际会议·行业动态'、'工艺路线·企业案例'、'市场预测·机构观点'
`language`	No	输出语言	zh
`confidence`	No	置信度过滤（A=公众号一手）
`response_format`	No	输出格式：markdown=人类阅读, 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"
+}

AddedSep 16, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds genuinely non-obvious traits: source material is Chinese-language, coverage is limited to 63 articles from 2026-04 onward, and 'A-grade' means first-hand rather than independently peer-reviewed. No contradiction 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 uses a clear Purpose/Guidelines/Limits/Examples structure and front-loads the main purpose. It is somewhat long, but each segment—coverage limits, A-grade clarification, and examples—carries real information that helps correct invocation. No filler.

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 6 optional parameters, an output schema, and a large sibling list, this description is complete: it defines scope, lists match targets, clarifies the confidence label, states coverage boundaries, and provides usage examples. Nothing an agent needs to call or interpret the result 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?

The schema covers all 6 parameters at 100%, so the description only needs to add value. It does so by explaining keyword matching semantics, giving concrete examples like query_articles(keyword='Pyrum'), and contextualizing category values and the meaning of A-grade. It does not walk through every parameter, but the schema already handles that.

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 opens with a specific verb and resource: 'search the first-hand research archive of the RCB industry WeChat official account,' followed by what is matched (title/topic/author/scope). This clearly distinguishes query_articles from siblings such as get_article (single-article retrieval) and other data-query tools.

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

Usage Guidelines4/5

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

The 'Guidelines' section gives concrete usage context: keyword matches certain fields, category filters to a single theme, and the coverage/date limits. It does not explicitly name alternative sibling tools or state when not to use query_articles, so it stops short of full when/when-not guidance.

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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