AleaBito / Serenity Skills

A suite of Claude / Codex agent skills distilled from @aleabitoreddit ("Serenity")'s entire public archive — ~11 months, 6,120 posts, 750 tickers (2025-07-02 → 2026-05-30). Track her, analyze like her, and anticipate where her attention is moving — grounded in real data, not vibes.

📊 Live dashboard / 实时看板: Lifetime attention tracker · 全周期注意力看板 — built on top of these skills · 基于这套技能制作

🌐 Language / 语言: English · 中文

claude-skill · agent-skill · aleabito · serenity · investing · stock-research · supply-chain · first-principles · x-api

English

What this is

Three interlocking skills that turn one prolific X (Twitter) research account into a reusable workflow:

The pipeline: follow-aleabito (data) → serenity-method (how she reasons) → serenity-radar (what she's likely to focus on next). Each later skill builds on the earlier one.

Install

1. Copy the skills into your agent's skills directory:
   hljs language-bash

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   cp -R skills/* ~/.codex/skills/      # Codex
   # or
   cp -R skills/* ~/.claude/skills/     # Claude Code
   

2. Node 18+ is required for the scripts.
3. X API token — put a bearer token in ~/.follow-aleabito/.env:
   hljs language-ini

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   X_BEARER_TOKEN=your_token_here
   

   The full-archive backfill (--archive) needs an X API project entitled to full-archive search (/2/tweets/search/all); the daily incremental fetch works on the standard user-timeline endpoint.
4. Point at your data dir (where the analytics CSVs live):
   hljs language-bash

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   export FOLLOW_ALEABITO_REPORTS_DIR="$HOME/aleabito-reports"
   

Quick start

# 1) Pull the latest posts incrementally (cheap; only fetches since the last run)
node skills/follow-aleabito/scripts/analyze-mentions.js --incremental --include-replies --resume

# 2) See where her attention is moving right now
node skills/serenity-radar/scripts/radar.js --window 14 --top 12

Sample radar output (trimmed):

## 🔥 Heating (attention momentum — recent vs prior mentions)
ticker=JBL   Δ=13  recent=25  prev=12
ticker=XFAB  Δ=12  recent=12  prev=0      # new entrant + heating = emerging focus
ticker=SIVE  Δ=10  recent=93  prev=83
## 🔄 Theme rotation
▲ Western supply chain / policy: +8     ▼ AI compute / neocloud: −12

Then ask your agent: "Analyze $SIVE like Serenity" → serenity-method produces the 5-block analysis. All output is 中文 by default, English on request.

Live dashboard

A self-contained, interactive lifetime research dashboard built on top of these skills — spanning her entire public archive, it maps attention momentum, mention structure (posts vs. replies vs. quotes), recent moves, and research priority across the tracked tickers, with linked price trends.

👉 Open the live dashboard — no login, no external dependencies. For tracking & research only, not investment advice.

How it was built

The skills are distilled from her complete public history, pulled with follow-aleabito's archive backfill (X API full-archive search). The empirical patterns in serenity-radar/references/patterns.md (theme-rotation logic, selection signature, catalyst playbook, conviction tells) are mined directly from those 6,120 posts — including the November-2025 drawdown (IREN −38% / NBIS −35%) she held through, which is why the radar's signals aren't overfit to a single up-only window.

Caveats & disclaimer

• Candidate generator, not an oracle. The radar predicts her interest, not price or correctness.
• Survivorship bias. Her archive over-weights names that worked; treat "she ramped X and it ran" as not evidence it repeats.
• Single-account fragility. One person, one style, one era.
• Not investment advice. For information tracking and research only. Do nothing with this that you wouldn't do after your own due diligence.

License

MIT.

中文

这是什么

三个环环相扣的技能,把一个高产的 X(推特)研究账号变成一套可复用的工作流:

管线: follow-aleabito(数据)→ serenity-method(她怎么推理)→ serenity-radar(她下一步可能看什么),后者建立在前者之上。

安装

1. 把技能复制到你 agent 的技能目录:
   hljs language-bash

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   cp -R skills/* ~/.codex/skills/      # Codex
   # 或
   cp -R skills/* ~/.claude/skills/     # Claude Code
   

2. 脚本需要 Node 18+。
3. X API token —— 在 ~/.follow-aleabito/.env 里放一个 bearer token:
   hljs language-ini

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   X_BEARER_TOKEN=你的token
   

   全档案回填(--archive)需要你的 X API 项目开通全档案搜索(/2/tweets/search/all);日常增量抓取用标准时间线端点即可。
4. 指定数据目录(分析 CSV 存放处):
   hljs language-bash

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   export FOLLOW_ALEABITO_REPORTS_DIR="$HOME/aleabito-reports"
   

快速上手

# 1) 增量拉取最新发帖(很省;只抓上次之后的)
node skills/follow-aleabito/scripts/analyze-mentions.js --incremental --include-replies --resume

# 2) 看她现在注意力往哪走
node skills/serenity-radar/scripts/radar.js --window 14 --top 12

然后对你的 agent 说:"用 Serenity 的方法分析 $SIVE" → serenity-method 会产出五段式分析。所有输出默认中文,可按需出英文。

实时看板

一个基于这套技能制作、自包含的交互式 全周期(lifetime)研究看板——覆盖她的全部公开历史,把注意力动量、提及结构(发帖 vs. 回复 vs. 引用)、近期变化和研究优先级在所有跟踪标的上可视化,并联动价格趋势。

👉 打开实时看板 —— 无需登录、无外部依赖;仅作跟踪与研究用途,不构成投资建议。

数据怎么来的

这些技能蒸馏自她的全部公开历史,用 follow-aleabito 的全档案回填(X API 全档案搜索)抓取。serenity-radar/references/patterns.md 里的经验模式(主题轮动逻辑、选股签名、催化剂打法、重仓信号)直接从这 6,120 条帖子里挖出——其中包含她扛过的 2025 年 11 月回撤(IREN −38% / NBIS −35%),这也是雷达信号没有过拟合到"单边上涨窗口"的原因。

风险与免责

• 候选发生器,不是预言机。 雷达预测的是她的兴趣,不是价格或对错。
• 幸存者偏差。 她的档案天然偏向"成功的标的";别把"她加注 X 然后涨了"当成会重演的证据。
• 单账号脆弱性。 一个人、一种风格、一个时代。
• 不构成投资建议。 仅作信息跟踪与研究用途;请以你自己的尽调为准。

许可

MIT。

Built with the follow-aleabito · serenity-method · serenity-radar skills. Not affiliated with @aleabitoreddit. 与 @aleabitoreddit 无隶属关系。