[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-84201":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":9,"language":10,"languages":9,"totalLinesOfCode":9,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":14,"subscribersCount":14,"size":14,"stars1d":15,"stars7d":12,"stars30d":12,"stars90d":14,"forks30d":14,"starsTrendScore":16,"compositeScore":17,"rankGlobal":9,"rankLanguage":9,"license":18,"archived":19,"fork":19,"defaultBranch":20,"hasWiki":21,"hasPages":19,"topics":22,"createdAt":9,"pushedAt":9,"updatedAt":37,"readmeContent":38,"aiSummary":9,"trendingCount":14,"starSnapshotCount":14,"syncStatus":39,"lastSyncTime":40,"discoverSource":41},84201,"aleabito-serenity-skills","lanfuli\u002Faleabito-serenity-skills","lanfuli","Claude\u002FCodex agent skills distilled from @aleabitoreddit (Serenity)'s full public archive — track her, analyze like her, anticipate her next focus. Bilingual 中文\u002FEnglish.",null,"JavaScript",67,10,57,0,3,16,55.12,"MIT License",false,"main",true,[23,24,25,26,27,28,29,30,31,32,33,34,35,36],"agent-skill","aleabito","anthropic","buffett","claude-code","claude-skill","equity-research","fintech","first-principles","investing","serenity","stock-research","supply-chain","x-api","2026-06-12 04:01:43","# AleaBito \u002F Serenity Skills\n\n> A suite of **Claude \u002F Codex agent skills** distilled from [@aleabitoreddit](https:\u002F\u002Fx.com\u002Faleabitoreddit) (\"Serenity\")'s **entire public archive** — ~11 months, 6,120 posts, 750 tickers (2025-07-02 → 2026-05-30).\n> Track her, analyze *like* her, and anticipate where her attention is moving — grounded in real data, not vibes.\n\n**📊 Live dashboard \u002F 实时看板:** **[Lifetime attention tracker · 全周期注意力看板](https:\u002F\u002Flanfuli.github.io\u002Ffollow-aleabito-skill\u002Freports\u002Faleabito-60d-dashboard.html)** — built on top of these skills · 基于这套技能制作\n\n**🌐 Language \u002F 语言:** **[English](#english)** · **[中文](#中文)**\n\n`claude-skill` · `agent-skill` · `aleabito` · `serenity` · `investing` · `stock-research` · `supply-chain` · `first-principles` · `x-api`\n\n---\n\n\u003Ca name=\"english\">\u003C\u002Fa>\n## English\n\n### What this is\nThree interlocking skills that turn one prolific X (Twitter) research account into a reusable workflow:\n\n| Skill | What it does | Key command |\n| --- | --- | --- |\n| **`follow-aleabito`** | **Data layer.** Fetches her posts via the X API, builds a beginner-friendly digest, cumulative ticker-mention analytics, and a durable research map. Includes a full-archive backfill. | `node skills\u002Ffollow-aleabito\u002Fscripts\u002Fanalyze-mentions.js --incremental --resume` |\n| **`serenity-method`** | **Her analysis method, generalized.** Apply her style to *any* stock: critical-chokepoint \u002F supply-chain-OSINT discovery → first principles → a Buffett-style quality gate (fields default to `unverified`) → narrative-vs-fundamentals hygiene → `research-map` vs `investable-conclusion`. | (invoked by request: \"analyze $X like Serenity\") |\n| **`serenity-radar`** | **Where her attention is going.** Reads the mention archive for attention momentum (heating tickers, new entrants, conviction core, theme rotation) and generates candidates in her style — a *candidate generator + checklist*, never an oracle. | `node skills\u002Fserenity-radar\u002Fscripts\u002Fradar.js --window 14` |\n\n**The pipeline:** `follow-aleabito` (data) → `serenity-method` (how she reasons) → `serenity-radar` (what she's likely to focus on next). Each later skill builds on the earlier one.\n\n### Install\n1. **Copy the skills** into your agent's skills directory:\n   ```bash\n   cp -R skills\u002F* ~\u002F.codex\u002Fskills\u002F      # Codex\n   # or\n   cp -R skills\u002F* ~\u002F.claude\u002Fskills\u002F     # Claude Code\n   ```\n2. **Node 18+** is required for the scripts.\n3. **X API token** — put a bearer token in `~\u002F.follow-aleabito\u002F.env`:\n   ```\n   X_BEARER_TOKEN=your_token_here\n   ```\n   The full-archive backfill (`--archive`) needs an X API project entitled to **full-archive search** (`\u002F2\u002Ftweets\u002Fsearch\u002Fall`); the daily incremental fetch works on the standard user-timeline endpoint.\n4. **Point at your data dir** (where the analytics CSVs live):\n   ```bash\n   export FOLLOW_ALEABITO_REPORTS_DIR=\"$HOME\u002Faleabito-reports\"\n   ```\n\n### Quick start\n```bash\n# 1) Pull the latest posts incrementally (cheap; only fetches since the last run)\nnode skills\u002Ffollow-aleabito\u002Fscripts\u002Fanalyze-mentions.js --incremental --include-replies --resume\n\n# 2) See where her attention is moving right now\nnode skills\u002Fserenity-radar\u002Fscripts\u002Fradar.js --window 14 --top 12\n```\nSample radar output (trimmed):\n```\n## 🔥 Heating (attention momentum — recent vs prior mentions)\nticker=JBL   Δ=13  recent=25  prev=12\nticker=XFAB  Δ=12  recent=12  prev=0      # new entrant + heating = emerging focus\nticker=SIVE  Δ=10  recent=93  prev=83\n## 🔄 Theme rotation\n▲ Western supply chain \u002F policy: +8     ▼ AI compute \u002F neocloud: −12\n```\nThen ask your agent: *\"Analyze $SIVE like Serenity\"* → `serenity-method` produces the 5-block analysis. All output is **中文 by default, English on request**.\n\n### Live dashboard\nA 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.\n\n👉 **[Open the live dashboard](https:\u002F\u002Flanfuli.github.io\u002Ffollow-aleabito-skill\u002Freports\u002Faleabito-60d-dashboard.html)** — no login, no external dependencies. For tracking & research only, not investment advice.\n\n### How it was built\nThe 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\u002Freferences\u002Fpatterns.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% \u002F NBIS −35%) she held through, which is why the radar's signals aren't overfit to a single up-only window.\n\n### Caveats & disclaimer\n- **Candidate generator, not an oracle.** The radar predicts *her interest*, not price or correctness.\n- **Survivorship bias.** Her archive over-weights names that worked; treat \"she ramped X and it ran\" as *not* evidence it repeats.\n- **Single-account fragility.** One person, one style, one era.\n- **Not investment advice.** For information tracking and research only. Do nothing with this that you wouldn't do after your own due diligence.\n\n### License\n[MIT](LICENSE).\n\n---\n\n\u003Ca name=\"中文\">\u003C\u002Fa>\n## 中文\n\n### 这是什么\n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:\n\n| 技能 | 作用 | 关键命令 |\n| --- | --- | --- |\n| **`follow-aleabito`** | **数据层。** 用 X API 抓取她的发帖,生成小白友好的简报、累计提及分析,以及持久的研究地图;含全档案回填。 | `node skills\u002Ffollow-aleabito\u002Fscripts\u002Fanalyze-mentions.js --incremental --resume` |\n| **`serenity-method`** | **她的分析方法,通用化。** 把她的风格套到*任意*股票:关键卡点 \u002F 供应链 OSINT 发现 → 第一性原理 → Buffett 五问质量门(默认 `unverified`)→ 叙事 vs 基本面卫生 → `研究地图` vs `可投资结论`。 | (按需调用:\"用 Serenity 的方法分析 $X\") |\n| **`serenity-radar`** | **她的注意力流向。** 从提及档案算注意力动量(升温标的、新进、重仓核心、主题轮动),并按她的风格生成候选——**候选发生器 + 检查清单**,不是预言机。 | `node skills\u002Fserenity-radar\u002Fscripts\u002Fradar.js --window 14` |\n\n**管线:** `follow-aleabito`(数据)→ `serenity-method`(她怎么推理)→ `serenity-radar`(她下一步可能看什么),后者建立在前者之上。\n\n### 安装\n1. **把技能复制**到你 agent 的技能目录:\n   ```bash\n   cp -R skills\u002F* ~\u002F.codex\u002Fskills\u002F      # Codex\n   # 或\n   cp -R skills\u002F* ~\u002F.claude\u002Fskills\u002F     # Claude Code\n   ```\n2. 脚本需要 **Node 18+**。\n3. **X API token** —— 在 `~\u002F.follow-aleabito\u002F.env` 里放一个 bearer token:\n   ```\n   X_BEARER_TOKEN=你的token\n   ```\n   全档案回填(`--archive`)需要你的 X API 项目开通**全档案搜索**(`\u002F2\u002Ftweets\u002Fsearch\u002Fall`);日常增量抓取用标准时间线端点即可。\n4. **指定数据目录**(分析 CSV 存放处):\n   ```bash\n   export FOLLOW_ALEABITO_REPORTS_DIR=\"$HOME\u002Faleabito-reports\"\n   ```\n\n### 快速上手\n```bash\n# 1) 增量拉取最新发帖(很省;只抓上次之后的)\nnode skills\u002Ffollow-aleabito\u002Fscripts\u002Fanalyze-mentions.js --incremental --include-replies --resume\n\n# 2) 看她现在注意力往哪走\nnode skills\u002Fserenity-radar\u002Fscripts\u002Fradar.js --window 14 --top 12\n```\n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**。\n\n### 实时看板\n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。\n\n👉 **[打开实时看板](https:\u002F\u002Flanfuli.github.io\u002Ffollow-aleabito-skill\u002Freports\u002Faleabito-60d-dashboard.html)** —— 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。\n\n### 数据怎么来的\n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\u002Freferences\u002Fpatterns.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% \u002F NBIS −35%),这也是雷达信号没有过拟合到\"单边上涨窗口\"的原因。\n\n### 风险与免责\n- **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。\n- **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。\n- **单账号脆弱性。** 一个人、一种风格、一个时代。\n- **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。\n\n### 许可\n[MIT](LICENSE)。\n\n---\n\n*Built with the [follow-aleabito](skills\u002Ffollow-aleabito) · [serenity-method](skills\u002Fserenity-method) · [serenity-radar](skills\u002Fserenity-radar) skills. Not affiliated with @aleabitoreddit. 与 @aleabitoreddit 无隶属关系。*\n",2,"2026-06-11 04:12:34","CREATED_QUERY"]