stock-event-driven-analysis

---

name: stock_event_driven_analysis description: Use this standalone stock strategy skill for 事件驱动 (event_driven) analysis. Accept one or more A-share stock codes, Chinese stock names, US stock tickers, or Hong Kong stock codes, collect market/news data, and produce a Codex-readable Markdown report focused on the 事件驱动 strategy. Source strategy: ~/daily_stock_analysis/strategies/event_driven.yaml.

事件驱动 Stock Analysis Skill

This skill is a strategy-specific variant of stock_ai_analysis. It uses the same bundled analyzer structure. User config, generated prompts, reports, and final reports for this strategy live under:

~/.stock_analysis/event_driven/

Downloaded market-data caches are shared across strategies under ~/.stock_analysis/cache/ so users do not need to fetch the same data repeatedly.

Strategy Source

• Source file: ~/daily_stock_analysis/strategies/event_driven.yaml
• Strategy id: event_driven
• Display name: 事件驱动
• Category: framework
• Aliases: 事件驱动, 催化, 催化事件
• Required source tools: search_stock_news, get_realtime_quote, analyze_trend
• Summary: 围绕业绩、政策、并购、订单、产品发布等事件，评估催化强度、兑现概率和风险边界。

Workflow

1. Work only inside this skill directory. Do not import, inspect, or depend on files outside it during normal analysis.
2. The script creates and reads user config at ~/.stock_analysis/event_driven/.env. Always run config check first:

python scripts/analyze.py --check-config

3. First-run hard rule: if --check-config shows CONFIG_CREATED: yes, explicitly tell the user initialization config is required before any analysis. Do not run --stocks in the same turn.
4. Incomplete-config hard rule: if required capability keys are missing for the user request, stop and ask the user to complete configuration using references/configuration.md before running analysis. Never run partial/incomplete analysis.
5. Ask for stock codes, names, or tickers if not supplied. Accept 600487, 北方华创, AAPL, 00700.HK, or mixed input like 北方华创,600487,AAPL,00700.HK.
6. Only after configuration is complete, run analysis:

python scripts/analyze.py --stocks <codes>

Use --no-llm for data-only smoke runs. Use --send-email only after the user confirms email delivery. Use --no-email for validation runs when EMAIL_ENABLED=true.

7. Open the latest prompt files under ~/.stock_analysis/event_driven/prompts/, use the current Codex agent to generate the final analysis, and write that analysis to a Markdown file under ~/.stock_analysis/event_driven/final_reports/.
8. The final analysis must apply the strategy rules below. Do not return a generic stock report when this skill is invoked.
9. Send email only from a finalized current-agent report:

python scripts/analyze.py --send-final-report ~/.stock_analysis/event_driven/final_reports/<report>.md

If a generated base report exists, merge the final analysis back into the original report before sending:

python scripts/analyze.py --send-final-report ~/.stock_analysis/event_driven/final_reports/<report>.md --base-report ~/.stock_analysis/event_driven/reports/<base_report>.md

Strategy Rules

事件驱动策略（Event Driven Strategy）

适用场景：

• 公司或行业出现明确事件催化，如业绩预告、订单中标、并购重组、政策落地、产品发布、监管处罚、诉讼等。
• 需要判断事件是短期交易催化、长期基本面改善，还是利好兑现。

分析框架：

1. 事件分类

   • 使用 search_stock_news 梳理近期关键事件。
   • 将事件分为：业绩类、政策类、订单/产品类、资本运作类、监管/风险类。
   • 明确事件发生时间，过期或时间未知的信息不能作为主要依据。

2. 影响路径

   • 判断事件影响的是收入、利润率、估值、融资能力、市场份额，还是仅影响情绪。
   • 对重大订单或政策利好，要说明兑现周期和不确定性。
   • 对监管、减持、处罚、诉讼等事件，风险优先。

3. 市场反应

   • 使用 get_realtime_quote 和 analyze_trend 判断事件是否已被价格充分反映。
   • 放量上涨但未过关键阻力，可等待确认。
   • 高位放量滞涨或利好后冲高回落，应警惕兑现压力。

4. 交易计划

   • 事件未兑现前，强调仓位控制和时间窗口。
   • 事件兑现后，重新评估是否从“预期交易”切换为“业绩验证”。
   • 对负面事件，先看风险释放是否充分，再考虑反弹。

输出要求：

• 明确事件性质：利好 / 利空 / 中性 / 不确定。
• 给出事件可信度、兑现周期、已反映程度。
• 操作建议必须包含失效条件，如公告不及预期、跌破关键支撑或事件热度消退。

评分调整建议：

• 高可信正向事件且价格尚未充分反映：sentiment_score +14
• 正向事件已大幅兑现：sentiment_score -6
• 负面事件仍在发酵：sentiment_score -15
• 事件影响不清晰或信息冲突：维持中性并降低置信度

Guardrails

• Never print real API keys, passwords, webhook URLs, or tokens.
• Ask before overwriting an existing ~/.stock_analysis/event_driven/.env value.
• Ask before sending email. Do not enable EMAIL_ENABLED=true unless the user explicitly wants automatic delivery.
• Do not block the user on optional keys. Offer a skip path and explain the consequence.
• Required-capability keys are not optional. If missing, stop and ask for config instead of running degraded analysis.
• First run always requires an explicit initialization prompt to the user before analysis.
• Never run partial or incomplete functionality; this is mandatory.
• Explain failures by impact: blocking, fallback succeeded, or data-quality degradation.
• Do not call local Hermes or other local agent CLIs from this skill. The current Codex agent is responsible for reading generated prompt files and writing the final analysis.
• Reports and emails must contain the strategy analysis result, not raw prompt context.

Bundled Resources

• scripts/analyze.py: deterministic entry point.
• scripts/stock_agent/: self-contained helper functions for config, data, search, LLM, and report rendering.
• scripts/stock_agent/data.py: strategy-local data extraction code that reuses the shared ~/.stock_analysis/cache/ directory to avoid duplicate downloads across strategies.
• assets/env.example: template copied to ~/.stock_analysis/event_driven/.env on first run.
• requirements.txt: Python dependency list.
• references/configuration.md: API-key setup details for this strategy folder.
• references/reporting.md: report and interface-status interpretation.