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AkTools MCP Server

by aahl

给出投资建议

trading_suggest

Generates AI-powered trading suggestions (buy, sell, or hold) with confidence scores and reasoning for stocks and cryptocurrencies.

Instructions

基于AI对其他工具提供的数据分析结果给出具体投资建议

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes股票代码或加密币种
actionYes推荐操作: buy/sell/hold
scoreYes置信度,范围: 0-100
reasonYes推荐理由

Implementation Reference

  • The @mcp.tool decorator registers 'trading_suggest' as a tool with title '给出投资建议' and description.
    @mcp.tool(
        title="给出投资建议",
        description="基于AI对其他工具提供的数据分析结果给出具体投资建议",
    )
  • The handler function 'trading_suggest' accepts symbol, action, score, and reason parameters and returns them as a dictionary. This is a simple data-passing tool that relays AI-generated investment advice.
    def trading_suggest(
        symbol: str = Field(description="股票代码或加密币种"),
        action: str = Field(description="推荐操作: buy/sell/hold"),
        score: int = Field(description="置信度,范围: 0-100"),
        reason: str = Field(description="推荐理由"),
    ):
        return {
            "symbol": symbol,
            "action": action,
            "score": score,
            "reason": reason,
        }
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral transparency. It only states the tool gives suggestions but does not disclose what actions it performs (e.g., whether it records, computes, or retrieves). The schema suggests inputting a suggestion, which conflicts with the 'giving' behavior, adding opacity. A score of 2 indicates insufficient disclosure beyond the basic purpose.

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

Conciseness3/5

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

The description is a single sentence, which is concise but lacks structure. It could benefit from separate sections for usage, behavior, or parameter context. While not verbose, the brevity sacrifices clarity, especially given the schema mismatch. A score of 3 reflects minimal effort with room for better organization.

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

Completeness2/5

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

Given the complexity introduced by the schema mismatch (the tool appears to receive rather than give suggestions), the description is incomplete. It does not explain how the tool uses the inputs or what output it produces, and no output schema is provided. The tool's actual function remains unclear. A score of 2 indicates significant gaps in contextual information.

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?

The input schema has 100% coverage with descriptions for all four parameters (symbol, action, score, reason). The description adds no additional meaning beyond what the schema already provides. Since schema coverage is high, a baseline of 3 is appropriate. The tool does not enhance parameter understanding further.

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

Purpose3/5

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

The description states it gives investment suggestions based on AI analysis, which is a clear verb+resource. However, the input schema requires action, score, and reason as inputs, suggesting the tool expects the suggestion details from the agent rather than generating them. This mismatch between description and schema reduces clarity, making the purpose ambiguous. A score of 3 reflects the central idea is present but contradicted by the schema.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives. The description implies it should be used after other data tools have provided analysis, but it does not state prerequisites or situations where this tool should be avoided. This lack of guidance leaves the agent without clear usage 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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