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kydlikebtc

binance-mcp-server

by kydlikebtc

binance_analyze_portfolio_risk

Analyze portfolio margin account risk, examining margin usage, positions, P&L, and asset quality to determine risk level and provide optimization recommendations.

Instructions

📊 投资组合风险分析 - 统一账户全面体检

🔍 功能说明: 深度分析统一账户(Portfolio Margin)的风险状况,包括保证金使用率、持仓分布、盈亏状态、资产质量等多维度风险评估。提供专业的风险等级判定和优化建议,是大额资金和专业机构的必备风控工具。

⚠️ 重要提醒: • 综合风险:统一账户风险共享,单一品种波动可能影响全账户 • 动态评估:市场波动会实时影响风险指标和保证金比例 • 相关性风险:不同资产间存在相关性,需要考虑系统性风险 • 流动性风险:部分持仓在市场异常时可能面临流动性不足

🎯 适用场景: • 大额资金投资组合的定期风险审查 • Portfolio Margin用户的保证金优化 • 机构投资者的风险管控和报告 • 个人投资者的资产配置健康检查

📋 输出示例: 分析完成后将返回:

📊 投资组合风险分析报告

⚖️ 整体风险评估:
账户总资产:156,847.50 USDT
风险等级:🟡 中等风险
保证金健康度:良好
建议操作:适度调整

💰 保证金状况:
总保证金:125,847.50 USDT
可用保证金:58,234.75 USDT (46.3%)
已用保证金:67,612.75 USDT (53.7%)
保证金使用率:53.7% (适中水平)

📈 持仓分析:
持仓品种:15个合约 + 8种现货
总仓位价值:234,567.89 USDT
净敞口:+89,234.56 USDT (偏多头)
集中度风险:BTC占比32.5% (偏高)

💸 盈亏状况:
总未实现盈亏:-2,450.75 USDT (-1.56%)
盈利仓位:7个 (+5,234.25 USDT)
亏损仓位:8个 (-7,685.00 USDT)
最大单笔亏损:-2,156.75 USDT (BTC多头)

🎯 资产质量:
主流资产占比:87.5% (优质)
山寨币占比:12.5% (可控)
稳定币比例:23.4% (偏低)
流动性评级:高流动性资产为主

⚡ 风险预警:
🟡 保证金使用率偏高:建议控制在50%以下
🟡 BTC集中度过高:建议适度分散配置
🔴 未实现亏损较大:需要重新评估止损策略
🟢 资产质量良好:主要持有优质标的

📊 压力测试:
-10%极端下跌:保证金比例降至142%
-20%系统性风险:可能触发部分强平
+15%市场反弹:预计盈利+23,456 USDT
波动率冲击:当前配置可承受25%波动

💡 优化建议:

🔹 保证金管理:
建议增加10,000 USDT保证金缓冲
或适度减少15%仓位规模
保持可用保证金在总资产30%以上

🔹 资产配置调整:
减少BTC集中度至25%以下
增加稳定币配置至30%
考虑加入负相关性资产对冲

🔹 风险控制:
为大额亏损仓位设置止损点
建立系统性风险预警机制
定期进行压力测试和再平衡

🎯 执行优先级:
1. 立即:为BTC多头设置止损
2. 本周:增加保证金或减仓15%
3. 本月:重新平衡资产配置比例
4. 持续:建立定期风险监控机制

⚠️ 关键风险提醒:
当前账户风险可控但需要积极管理。
建议密切关注市场系统性风险信号。
及时调整仓位应对流动性紧张局面。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description carries the full burden of transparency. It discloses that the tool analyzes shared risk across the unified account, accounts for dynamic market fluctuations, correlation risks, and liquidity risks, and provides a detailed sample report. This gives the agent a clear understanding of the tool's behavior and output without requiring annotation support.

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 quite lengthy, with extensive emoji formatting, repetitive warnings (e.g., '重要提醒' and '关键风险提醒'), and a very large output example. While it is well-structured and front-loaded with the core purpose, it could be more concise without losing essential detail.

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?

The tool is complex with a rich output, and the description compensates for the lack of output schema and annotations by including a comprehensive example report that covers risk ratings, margin status, position analysis, stress testing, and optimization recommendations. It also lists applicable scenarios and risk warnings, making the tool's behavior fully understandable.

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, and the schema coverage is 100%. The description focuses on the analysis scope and output format rather than parameter semantics, which is appropriate—there are no parameters to clarify. It meets the baseline for parameter-free tools.

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 explicitly states this tool performs portfolio risk analysis on Portfolio Margin accounts, covering margin usage, position distribution, P&L, and asset quality. This clearly differentiates it from sibling tools like binance_portfolio_account or binance_futures_positions, which provide raw data rather than risk assessment.

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 a dedicated '适用场景' section listing concrete use cases such as periodic risk review, margin optimization, institutional risk control, and personal asset health checks. While it doesn't explicitly name alternative tools, the context clearly indicates when this analysis tool is appropriate versus simple account/position queries.

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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