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China Recalls

by io.github.pipeworx-io
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China Search Recalls

china_search_recalls
Read-onlyIdempotent

Search product recall announcements from the State Administration for Market Regulation (SAMR), China: about 1,400 announcements since 2018, newest first. Mostly motor vehicles and motorcycles, plus some consumer goods (power banks, vacuum flasks). Filter by title text (Chinese company or product, some English brands), inferred category, and date range. Returns id, title, date and category; pass an id to china_get_recall for the full notice.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "limit": 5,
      "query": "充电宝"
    },
    "name": "china_search_recalls"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoLatest announcement date, YYYY-MM-DD.
fromNoEarliest announcement date, YYYY-MM-DD.
limitNo1-50, default 20.
queryNoText in the announcement title, e.g. 特斯拉, 充电宝, 小米, or tesla / power bank.
offsetNoSkip this many matches, for paging.
categoryNoInferred from the title. Default all.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive). The description adds real behavioral context beyond them: dataset size (~1,400 since 2018), ordering (newest first), and content composition (mostly vehicles, some consumer goods).

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?

Four tight sentences, front-loaded with corpus scope, then composition, then filtering, then return/routing. Every sentence carries distinct information with no redundancy.

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?

No output schema, but the description compensates by naming the returned fields (id, title, date, category) and explaining how to escalate to the full notice. An agent has everything needed to call it correctly.

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?

Schema description coverage is 100% and already documents every parameter including examples for query and enum values for category. The description restates the filter dimensions and 'inferred' category but adds no syntax or format detail beyond the schema, so baseline 3 applies.

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?

States a specific verb (Search) and resource (SAMR product recall announcements in China), and distinguishes itself from the sibling china_get_recall by naming it for full-notice retrieval. An agent can tell exactly what corpus this queries.

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?

Clear context for use (title text, category, date-range filtering) and an explicit routing to china_get_recall when a full notice is needed via a returned id. No explicit 'when-not' exclusions, but the alternative is named with the condition that selects it.

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

All China Recalls toolsInspect
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