SkillFoxx

Serenity Bottleneck Hunter skill

A skill researches supply chains around an investment theme, collects company candidates and builds a dated, source-linked report.

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Skill

Extended access

Why this level

  • The skill retrieves market data and writes reports and research CSVs rather than placing orders.
All reasons and checks

mrjie7205/serenity-bottleneck-hunterAuthor:mrjie7205

Install

In your terminal, with SkillFoxx CLI

npx skillfoxx add skills/serenity-bottleneck-hunter

Detects the agents on your machine, shows the access level and pins the version.

Other ways to install

Access and checks

How we review

Extended accessThe tool runs code or makes network calls and only reads external data.

  • The skill retrieves market data and writes reports and research CSVs rather than placing orders.

This is third-party code. Review the repository files before installing.

What it does

Serenity Bottleneck Hunter researches an investment theme through its supply chain. The agent maps dependencies, identifies potential bottlenecks and checks companies against source data. A standalone HTML report records reasoning, reconsideration conditions and references. Bundled scripts retrieve prices, validate tickers and reconcile report figures with input data. Dated tracking records support later evaluation. An optional local dashboard displays history but is not required for the core skill.

Who it is for. For market researchers testing supply-chain hypotheses and retaining inspectable report evidence.

Good fit when

  • Map participants in an industry supply chain.
  • Validate candidate tickers and data dates.
  • Reconcile HTML-report figures with input data.
  • Retain a hypothesis with conditions for reconsideration.

Not a fit when

  • You need promised returns or a personal trading decision.
  • A historical demo would be treated as a current market assessment.
  • Prices would be guessed from model memory.

Example request

Analyze an educational supply-chain theme, showing sources and uncertainty without buy recommendations.

Limitations

Demos use dated historical snapshots; new research needs current sources and dates for every metric. Pricing scripts require dependencies and suitable data sources, sometimes with paid quotas. The method produces research candidates and can misread relationships or company valuation, so inspect primary documents. Reports and CSV records retain conclusions for later review; keep private research separate from public demo data.

How to disable. Remove the skill and stop any separately started dashboard. Retain or remove research CSVs, reports and configured schedules separately.

FAQ

Is it for code-performance bottlenecks?

No. It studies companies and supply-chain bottlenecks.

How do I run the demo?

Use `python scripts/run_demo.py` without credentials or network.

Is the dashboard required?

No. It supplements the independent core skill.

Is an EODHD API key mandatory?

Some prices can use yfinance; coverage and dependencies depend on the market.

How is a report checked?

`scripts/verify_report.py` validates structure, figures and tracking against input data.

Discussion

No questions or reviews yet.

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README in short

The skill requires data provenance and conditions for reconsidering a hypothesis. Historical archives do not automatically become current market data.

README badge

Original SKILL.md

---
name: serenity-bottleneck-hunter
description: 给定一个投资主题/趋势,复用交易者 Serenity(@aleabitoreddit)的"供应链瓶颈逆向映射"方法论,独立挖出被市场忽视的上游瓶颈股(而非分析他已喊过的标的)。当用户给出一个主题(如"AI 数据中心电力""人形机器人""HBM 内存")并想要候选标的+论证时使用。仅供研究教育,非投资建议。
---

# Serenity Bottleneck Hunter

把一个**投资主题**转成一份**被忽视的上游瓶颈候选股名单 + 论证 + 目标价/时间框架**。核心不是抄 Serenity 的票,而是**复用他的逻辑去选新股**。

> 📓 每条纪律是怎么用一次真实翻车换来的,见 `reference/lessons.md`。本文件只讲"做什么";完整事故复盘在那边,用 `〔… → lessons.md#锚点〕` 指过去。

## 何时用
- 用户给出一个主题/趋势,想要"沿这个方向能买什么"。
- 用户给一个上游环节/材料,想找对应的瓶颈公司。
- ❌ 不要用于:已知标的的纯财务分析、抄作业式"他买了啥"。

## 核心理念
> 逆向拆解供应链,在机构与分析师发现之前,埋伏那个**无人察觉的上游瓶颈**,用催化剂兑现。
> alpha 来自"**早于机构发现主题**",不是抄到最低点。

---

## v0.2 工具入口

- 首次安装后可执行 `python scripts/run_demo.py`：不联网的历史演示，输出与正式跟踪表分开；说明见 [examples/README.md](examples/README.md)。演示不替代真实研究。
- 实际 A 股／美股／港股取价与估值设置见 [reference/DATA_SOURCES.md](reference/DATA_SOURCES.md)。保留来源、行情日期及质量提醒；不得按跳空幅度自行猜除权。
- 报告 SPEC 中相对路径从本技能根目录解析；可用 `tracking_file` 选择自己的 CSV。现有默认路径兼容保留。`shell_from` 缺省时使用内置模板，无需私库或驾驶舱。
- 发布前可用 `python scripts/verify_report.py <报告> --scan <输入> --tracking <跟踪表> --strict` 完整对账。严格模式的输入缺失和数字错配必须先解决。

## 可选驾驶舱

只有用户需要管理、跟踪或复盘已有研究时，才使用 [cockpit/README.md](cockpit/README.md) 的本地驾驶舱。核心研究流程不依赖它。

默认 `python cockpit/run.py` 读取只读历史演示，不抓取行情。用户自己的研究须明确指定目录；报告 SPEC 的 `out` 与 `tracking_file` 应指向该目录。取价、告警核对和定时任务分别由用户手动触发或显式启用。驾驶舱的“猎手／覆盖”是显示范围，不是龙头视角。

个人目录的星级用 `tracking/cross_theme_scan.py --input <个人跟踪表> --output <个人星级表>` 重建，避免把公库历史样本的星级混入个人研究。

## 工作流(7 步)

**Step 1 · 确认资本开支确定性**
这个主题的钱为什么"一定"会花?规模、周期多长?需求确定性 > 个股故事性。先归类:**Bottleneck(瓶颈)/ Disruption(颠覆)/ Evolution(演进)**?(本 skill 主攻 Bottleneck)
- **标明需求来源**:政府/国防(节奏慢、看订单与预算周期)还是商业(超大规模厂商 capex、节奏快)?二者估值锚与择时节奏不同,Step 6/7 据此调整。

**Step 2 · 逆向拆链 + 广扫纪律(5 层产业链 + 跨主题 root + 可选第 6 层独有 IP)**
列出 **5 层** 从下游到上游:**下游对照 → 中游系统 → 中游器件 → 上游设备 → 上游材料/代工**。**跳过人人都盯的下游龙头**。

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