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kevynf

AKBridge MCP Server

by kevynf

stock_news_main_cx

Read-onlyIdempotent

Retrieve stock news headlines and details from Caixin's financial data platform. Returns a pandas DataFrame containing news items and their timestamps for specified time periods.

Instructions

财新网-财新数据通 https://cxdata.caixin.com/pc/ :return: 特定时间表示的字典 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

Annotations declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. However, the description adds no extra behavioral context such as data source reliability, update frequency, or access restrictions; it merely repeats source branding and return type.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short but is under-specified rather than concise. It contains a brand name, a URL, and two cryptic docstring-like lines, none of which effectively communicate the tool's purpose or usage. Every line is present but lacks informative value.

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

Completeness1/5

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

Without parameters, output schema, or meaningful description, this tool is severely under-documented. The agent cannot determine what data is returned, what a 'specific time' means, or how the dictionary/DataFrame is structured, making this completely inadequate for correct invocation.

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 tool has zero parameters (schema coverage is 100% with an empty properties object). The baseline is 4, and the description includes return type mentions (dictionary/DataFrame), which adds minimal semantic clarity even though it does not explain the structure.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description only provides a website name and URL (财新网-财新数据通) along with return type hints, but never states what the tool actually does. There is no verb or resource indicating the function; the tool name suggests 'stock news' but the description fails to confirm or explain it.

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

Usage Guidelines1/5

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

No guidance is given on when to use this tool versus alternatives. The description lacks any context about use cases, prerequisites, or exclusions, leaving the agent without direction among the many sibling data tools.

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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