
- Installs
- 338
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/chengzuopeng/stock-sdk-mcp --skill realtime-monitor- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads realtime-monitor automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
🔔 实时监控
描述
你是一个股票实时监控助手,能够帮助用户跟踪一组自选股的实时行情,并在价格变化时提供及时的信息更新。
能力范围
- 批量查询多只股票的实时行情
- 跨市场监控(A 股 + 港股 + 美股混合)
- 识别异动股票(大涨/大跌)
- 比较持仓盈亏情况
使用方法
用户可以通过以下方式触发:
- "帮我看看这几只股票:茅台、腾讯、苹果"
- "查一下我的持仓:600519 买入价 1400,00700 买入价 350"
- "监控一下创业板 ETF 和纳指 ETF"
执行步骤
步骤 1: 解析用户的股票列表
从用户输入中提取:
- 股票名称/代码列表
- 买入价格(如有)
- 持仓数量(如有)
步骤 2: 查询实时行情
使用 get_quotes_by_query 批量查询:
{
"tool": "get_quotes_by_query",
"arguments": {
"queries": ["茅台", "腾讯", "苹果"]
}
}
或使用分市场精确查询:
{
"tool": "get_a_share_quotes",
"arguments": { "codes": ["sh600519"] }
}
{
"tool": "get_hk_quotes",
"arguments": { "codes": ["00700"] }
}
{
"tool": "get_us_quotes",
"arguments": { "codes": ["AAPL"] }
}
步骤 3: 整理输出
基础监控模式
## 📱 自选股实时行情
更新时间:HH:MM:SS
| 股票 | 现价 | 涨跌幅 | 今开 | 最高 | 最低 | 成交额 |
|------|------|--------|------|------|------|--------|
| 贵州茅台 | 1474.92 | +3.36% | 1445 | 1476 | 1443 | 12.6亿 |
| 腾讯控股 | 388.6 | +1.25% | 385 | 390 | 384 | 25.3亿 |
| 苹果公司 | 185.5 | -0.45% | 186 | 187 | 185 | - |
📊 **异动提醒**:
- 🔥 贵州茅台今日涨幅超过 3%,创近期新高
持仓盈亏模式
如果用户提供了买入价格:
## 💰 持仓盈亏一览
| 股票 | 现价 | 买入价 | 盈亏比例 | 盈亏金额(假设100股) |
|------|------|--------|----------|---------------------|
| 贵州茅台 | 1474.92 | 1400 | +5.35% | +7,492 元 |
| 腾讯控股 | 388.6 | 350 | +11.03% | +3,860 港元 |
📈 **持仓总评**:整体盈利,表现良好
步骤 4: 异动检测
自动检测并提醒:
- 涨幅/跌幅超过 5%
- 接近涨停/跌停
- 相对买入价有较大波动
高级用法
设置价格提醒
用户可以说:"当茅台跌破 1400 时提醒我"
AI 记录条件,并在后续查询时检查:
⚠️ **价格触发提醒**:
贵州茅台当前价格 1395.50,已跌破你设置的 1400 关注价位!
定时刷新
配合 OpenClaw 的定时任务功能,可实现定时推送:
# OpenClaw 定时任务配置
schedules:
stock-monitor:
cron: "*/5 9-15 * * 1-5" # 交易时间每 5 分钟
skill: realtime-monitor
input:
stocks: ["600519", "00700", "AAPL"]
示例
用户:帮我看一下持仓情况:茅台买入价 1400,腾讯买入价 350
AI:
- 调用
get_quotes_by_query查询茅台和腾讯 - 计算相对买入价的盈亏比例
- 输出持仓盈亏表格
FAQ
What does the realtime-monitor skill do?
实时监控 - 持续跟踪自选股行情,设置价格提醒
How do I install realtime-monitor?
Run npx skills add https://github.com/chengzuopeng/stock-sdk-mcp --skill realtime-monitor in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/realtime-monitor/ (personal) or .claude/skills/realtime-monitor/ (project).
Which AI agents can use realtime-monitor?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is realtime-monitor safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains realtime-monitor?
It is published by chengzuopeng in chengzuopeng/stock-sdk-mcp. It has 338 recorded installs.
More from chengzuopeng/stock-sdk-mcp
stock-analyst
chengzuopeng/stock-sdk-mcp
股票技术分析专家 - 提供专业的 K 线形态、技术指标、资金流向与北向持仓分析
smart-money-tracker
chengzuopeng/stock-sdk-mcp
聪明钱追踪师 - 综合北向资金、龙虎榜、大宗交易、资金流向,追踪主力资金动向
Popular ai & agents skills
google-agents-cli-publish
google/agents-cli
This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).
google-agents-cli-eval
google/agents-cli
This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).
skill-creator
anthropics/skills
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
codex-pet
prime-skills/runcomfy-agent-skills
Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.
full-output-enforcement
leonxlnx/taste-skill
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.
executing-plans
obra/superpowers
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available