query_index查询A股三大指数实时行情，包括上证指数、深证成指、创业板指的点位、涨跌幅和市场整体趋势。
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "query_index"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Input schema / additionalPropertiesAdded value: +falseInput schema / titleRemoved value: -"query_indexArguments"Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description must carry the behavioral burden. It does disclose that the data is '实时' (real-time) and that output includes an aggregated '市场整体趋势' judgment beyond raw quotes, which is useful. It does not state data-source latency, market-hours behavior (what happens when the market is closed), or any access constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that front-loads the action and scope, then lists the returned fields. No filler, no restatement of the title, and every clause adds information the agent needs.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with an output schema present, the description covers purpose, covered indices, and returned fields adequately; return-value details can be left to the schema. The only meaningful gap is behavioral edge cases such as non-trading-hours behavior or data freshness guarantees.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for 0 params applies. The description correctly implies a fixed, no-argument call covering all three indices at once.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource ('查询A股三大指数实时行情'), then enumerates the exact contents: the three named indices plus 点位, 涨跌幅, and 市场整体趋势. Because the scope is hard-limited to the three major indices, an agent can distinguish it from query_stock_quote (an individual-stock quote) without opening the schema, though the sibling is never named explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied: the phrase 'A股三大指数' signals this is the tool for benchmark/market overview queries rather than single-stock queries. There is no explicit when-to-use, when-not-to-use, or 'use query_stock_quote instead for individual stocks' routing statement.
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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