Stock Scheme Tracker 📈

个股投资策略跟踪器——将从分析报告中提取的个股投资策略持久化到一个本地 Markdown 文件，然后定期核对市场行情是否触发了建仓、止损或止盈条件，给出可操作的下一步建议。

两种模式：

• 保存模式（Save）：完成任意个股分析后（DCF 估值、巴菲特框架、技术分析等），自动从分析文本中提取建仓条件、止损线、目标价、退出信号、核心假设等关键字段，格式化后追加到策略跟踪文件。如果该股票已存在则更新而非重复添加。触发词：保存策略、跟踪这个票、记录建仓条件
• 核对模式（Check）：读取策略跟踪文件中所有已保存的策略，获取每只股票的最新行情数据（价格、PE 等），逐条比对建仓条件是否已触发（✅ 已触发 / ❌ 未触发 / ⚠️ 接近触发），检查退出信号是否出现，输出清晰的汇总表格和每只股票的具体操作建议。触发词：检查策略、核对建仓条件、看看哪些票可以买

兼容 OpenClaw / WorkBuddy / Claude Code 等 AI Agent 工具。仅需 Python 3 运行时，通过 STOCK_SCHEME_PATH 环境变量指定策略文件路径，脚本不做任何网络请求，核对模式的行情数据由 Agent 通过其金融数据工具或网络搜索获取。

Save per-stock investment strategies extracted from analysis reports into a persistent tracking file, then periodically check if market conditions have triggered any entry, stop-loss, or take-profit conditions. Provide actionable next-step recommendations.

Quick Start

Install

Copy the skill directory to your agent's skills folder:

# OpenClaw
cp -r stock-scheme-tracker ~/.openclaw/skills/

# WorkBuddy
cp -r stock-scheme-tracker ~/.workbuddy/skills/

# Claude Code (project-level)
cp -r stock-scheme-tracker .claude/skills/

Configure

Set the environment variable to point to your tracking file:

# Add to your shell profile (~/.zshrc, ~/.bashrc, etc.)
export STOCK_SCHEME_PATH="$HOME/Documents/stock/scheme.md"

Or configure via your agent's config:

// OpenClaw: ~/.openclaw/openclaw.json
{
  "skills": {
    "entries": {
      "stock-scheme-tracker": {
        "env": {
          "STOCK_SCHEME_PATH": "~/Documents/stock/scheme.md"
        }
      }
    }
  }
}

If STOCK_SCHEME_PATH is not set, the skill defaults to ~/Documents/stock/scheme.md.

Verify

echo $STOCK_SCHEME_PATH
# Should output your configured path

Workflow Decision Tree

1. Determine mode: Did the user just complete an analysis (→ save mode), or do they want to review existing strategies (→ check mode)?
2. Save mode: Extract strategy elements from the analysis, format them, and append to the scheme file.
3. Check mode: Read all strategies from the scheme file, fetch latest market data for each stock, evaluate every condition, and output a summary with next-step recommendations.

Save Mode

When to Use

• Immediately after completing any stock investment analysis (e.g., DCF valuation, Buffett framework, technical analysis, or any investment report).
• The user says "保存策略", "把策略记下来", "跟踪这个票", "save strategy", "track this stock", or any variant.

Extraction Rules

From the analysis text, extract these fields. If a field is not mentioned, mark it as "未明确" rather than fabricating.

Output Format

Append a new section to the scheme file (path from STOCK_SCHEME_PATH env var) using the exact format defined in references/scheme_format.md. Use Markdown table for entry conditions so they can be machine-parsed later.

Important

• If the stock already exists in the scheme file, update the existing section rather than duplicating it. Preserve historical entries by appending a date-stamped update note.
• After saving, briefly confirm to the user what was saved.

Check Mode

When to Use

• User says "检查策略", "核对建仓条件", "看看哪些票可以买", "策略跟踪", "check strategy", or any variant.
• Can be invoked standalone without any prior analysis.

Steps

1. Read the scheme file (path from STOCK_SCHEME_PATH env var).
2. For each tracked stock, fetch the latest market data (price, PE, key metrics). Use available financial data tools or web search.
3. Evaluate each entry_conditions row: compare current value vs target value.
4. Mark each condition as ✅ 已触发, ❌ 未触发, or ⚠️ 接近触发.
5. Check if any exit_signals have occurred.
6. Output a clean summary table and specific next-step recommendations per stock.

Output Format

## 策略核对报告 — 2026-04-23

### XX办公 (688XXX)
| 条件类型 | 目标 | 当前 | 状态 |
|----------|------|------|------|
| PE建仓 | ≤45-50 | 62.46 | ❌ 未触发 |
| 股价建仓 | 180-200 | 250 | ❌ 未触发 |

**建议**: 继续观察，等待PE回落至50以下或股价跌破200再考虑建仓。

Core Tasks

Here are natural-language prompts that trigger this skill:

• "我刚分析完XX办公，帮我保存策略"
• "检查一下我跟踪的股票，哪些条件触发了"
• "核对建仓条件"
• "跟踪策略"
• "把刚才的分析结论记录到策略跟踪文件"
• "I just finished analyzing Apple, save the strategy"
• "Check all my stock strategies"

Environment Variable Contract

Security & Guardrails

1. Local file only: Both scripts only read/write a local Markdown file specified by STOCK_SCHEME_PATH. No network calls are made by save_scheme.py or check_scheme.py.
2. Market data source: During check mode, market data is fetched via the agent's available financial data tools or web search. This involves querying public market quotes (stock codes and metric names only) — no private strategy content or position details are transmitted.
3. No trading execution: This skill provides analysis and recommendations only. It does NOT execute any trades or connect to brokerage accounts.
4. No credential collection: This skill only requires STOCK_SCHEME_PATH (a file path). It never asks for API keys, tokens, passwords, or any other credentials.
5. Data integrity: The save script uses atomic write patterns and preserves historical entries. Existing stock sections are updated in-place rather than overwritten.
6. Path validation: The scripts validate that STOCK_SCHEME_PATH points to a .md file and will create parent directories if needed.

Troubleshooting

Release Notes

• 1.1.0 — Fixed metadata consistency (top-level requires/env), added credential collection disclaimer, clarified market data query scope in security section.
• 1.0.0 — Initial release. Save and check modes with Markdown-based tracking file.

Links

• Scheme Format Reference
• Save Script
• Check Script

Publisher

• Publisher: @dc
• License: MIT-0
• Source: https://github.com/dcsight/