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AgentLadle MCP AKShare

get_sector_constituent

Read-onlyIdempotent

Retrieve constituent stocks of a sector by specifying its type (industry or concept) and Chinese name, e.g., '小金属'.

Instructions

Get stocks within a sector.

sector_name must be Chinese (e.g. "小金属"). Use get_sector_quote to find names. sector_name accepts Chinese names like "小金属", "白酒". get_sector_constituent(sector_type="industry", sector_name="小金属")

Args: sector_type: industry/concept sector_name: Sector name (Chinese, e.g. "小金属")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sector_nameYes
sector_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
hintNo
errorNo
cachedNo
sourceNo
statusYes
updated_atNo
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint. The description adds a key behavioral constraint: sector_name must be Chinese, which is not covered by annotations. It does not contradict 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 is structured with a brief phrase, then XML-like guidance and an Args list. It is somewhat verbose but front-loaded with the core purpose. Each section adds value.

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

Completeness4/5

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

Given the tool's simplicity (2 params, output schema exists) and annotations, the description is adequately complete. It explains the input constraints and provides examples. The return value is covered by the output schema.

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 0%, so the description carries the burden. The Args section provides basic semantics: sector_type is 'industry/concept' and sector_name is 'Sector name (Chinese, e.g. '小金属')'. This adds some meaning but is not very detailed.

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 'Get stocks within a sector', which is a specific verb and resource. It differentiates from siblings like get_sector_quote (which gets quotes) and get_index_constituent (index constituents).

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 provides when-to-use guidance via <strategy> and <critical_rules>, stating that sector_name must be Chinese and that get_sector_quote should be used to find names. This effectively guides the agent on 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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