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lolifamily

ashare-mcp

get_dividend_data

Fetch a stock's annual dividends: total cash per share and each payout's details for a specified year, handling multiple distributions and non-cash dividends.

Instructions

Fetch a year's dividends: annual cash total plus every payout's detail.

A year with several distributions has one entry per payout in payouts (full detail). annual_cash_per_share_pretax is their summed dividCashPsBeforeTax — the yearly total, so callers needn't add across rows. Within a single payout, semicolon-separated multi-values in the cash-dividend fields are already summed by the client.

annual_cash_per_share_pretax is None when the year had distributions but no cash (pure stock dividend / capital reserve conversion); read each payout's dividStocksPs / dividReserveToStockPs for those.

Args: code: Stock code. year: 4-digit year, e.g. '2023'. year_type: 'report' (announcement year) or 'operate' (ex-dividend year).

Returns: {code, year, annual_cash_per_share_pretax, payout_count, payouts}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes
yearYes
year_typeNoreport
Behavior5/5

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

No annotations are provided, so the description carries full burden. It details the behavior: returns annual total and payout details, explains that annual_cash_per_share_pretax is summed and can be None for non-cash distributions, and describes how semicolon-separated values are already summed. This is comprehensive.

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 well-structured with a summary, details, Args, and Returns sections. It is informative but contains slight redundancy (explaining annual_cash_per_share_pretax twice). Overall concise and front-loaded.

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?

There is no output schema, so the description must cover return value structure. It does so explicitly: '{code, year, annual_cash_per_share_pretax, payout_count, payouts}'. It also addresses edge cases (None for non-cash) and clarifies multi-value handling. Complete for 3 parameters with no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage. The description includes an 'Args:' section that explains each parameter's meaning and type (e.g., year is '4-digit year', year_type is 'report' or 'operate'). This adds crucial value 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 states explicitly 'Fetch a year's dividends: annual cash total plus every payout's detail.' It uses specific verbs and resources, and clearly distinguishes from sibling tools which cover different financial data (valuation, balance sheet, etc.).

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 description provides guidance on when to use the tool (to get dividend data) and explains how to interpret results, including handling of non-cash distributions and multi-values. However, it does not explicitly state when not to use or mention alternatives, though siblings are unrelated.

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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