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ER-EPR

futu-opend-mcp

by ER-EPR

get_industrial_chains

Browse industrial supply chains by market and keyword, view chain details for upstream/midstream/downstream, or find chains linked to a plate.

Instructions

Browse industrial/supply chains - 产业链. view: list (chains in a market, optional keyword), detail (one chain's upstream/midstream/downstream - pass chain_id), by_plate (chains linked to a plate - pass plate_id). market needed for list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
viewNolist
countNo
marketNo
keywordNo
chain_idNo
plate_idNo
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It describes the read-like operation (browse) and view modes, but does not mention side effects, authentication, rate limits, or pagination. The behavior is implied but not fully transparent.

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?

The description is extremely concise, using a single sentence with clear bullet-like formatting. It front-loads the main purpose and efficiently conveys all necessary view-specific instructions without any redundant or filler content.

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

Completeness3/5

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

Given the tool has 6 parameters and no output schema, the description provides a reasonable overview of input requirements and view outcomes. However, it lacks details on the return data structure, pagination behavior, or default values (e.g., count=20), which are important for the agent to fully understand the tool's output.

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?

With 0% schema description coverage, the description effectively explains the purpose of 5 out of 6 parameters (view, market, keyword, chain_id, plate_id) within the context of different views. Only the 'count' parameter is not explained. This adds significant meaning beyond the 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 browses industrial/supply chains and explicitly lists three distinct views (list, detail, by_plate) with their specific purposes. It differentiates from sibling tools like get_industrial_plate by focusing on chains rather than plates, aiding correct selection.

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

Usage Guidelines3/5

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

The description provides some usage guidelines, e.g., 'market needed for list' and which ID to pass for each view. However, it does not specify when to avoid this tool or mention alternative tools for similar tasks, leaving the agent without full decision-making context.

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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