[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-82160":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":16,"stars30d":17,"stars90d":14,"forks30d":14,"starsTrendScore":18,"compositeScore":19,"rankGlobal":9,"rankLanguage":9,"license":9,"archived":20,"fork":20,"defaultBranch":21,"hasWiki":22,"hasPages":20,"topics":23,"createdAt":9,"pushedAt":9,"updatedAt":24,"readmeContent":25,"aiSummary":26,"trendingCount":14,"starSnapshotCount":14,"syncStatus":27,"lastSyncTime":28,"discoverSource":29},82160,"serenity-aleabitoreddit","yan-labs\u002Fserenity-aleabitoreddit","yan-labs","Installable Serenity tweet archive + AI\u002Fsemi supply-chain skill. Install: npx skills add yan-labs\u002Fserenity-aleabitoreddit",null,"Python",284,43,4,0,6,209,252,54,83.93,false,"main",true,[],"2026-06-12 04:01:37","npx skills add yan-labs\u002Fserenity-aleabitoreddit\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fx.com\u002Faleabitoreddit\">\n    \u003Cimg src=\"assets\u002Fserenity-avatar.jpg\" alt=\"Serenity (@aleabitoreddit)\" width=\"112\" height=\"112\">\n  \u003C\u002Fa>\n\u003C\u002Fp>\n\n# serenity-aleabitoreddit\n\n[![skills.sh](https:\u002F\u002Fskills.sh\u002Fb\u002Fyan-labs\u002Fserenity-aleabitoreddit)](https:\u002F\u002Fskills.sh\u002Fyan-labs\u002Fserenity-aleabitoreddit)\n\nEverything distilled from **Serenity\n([@aleabitoreddit](https:\u002F\u002Fx.com\u002Faleabitoreddit))** — a public X trader and\nAI\u002Fsemiconductor *supply-chain* analyst known for tracing hyperscaler capex into\nupstream bottlenecks. His recurring research terrain includes optical\u002FCPO and\nphotonics, InP substrates and compound semis, memory\u002FHBM\u002FNAND, neocloud\nfinancing quality, AI power\u002Fgrid demand, robotics\u002Fphysical AI, and overlooked\ninternational supply-chain names.\n\nThis repo packages his public work into one self-contained research artifact:\n**the raw tweet archive**, **long-form article summaries**, a\n**period-by-period distillation**, and a ready-to-use **agent skill** that\napplies his analytical lens to US-stock ideas.\n\nBuilt from **5,625 tweets** spanning **2025-07-02 → 2026-05-30** plus **4 X\nArticles** published in **2026-01 → 2026-05**.\n\n> ⚠️ **Not financial advice. Decision-support only.** This skill never trades and\n> never places or cancels orders. Serenity's self-reported returns are unverified\n> and carry obvious survivorship\u002Fselection bias; his names are volatile\n> micro\u002Fsmall-caps. Use the lens to ask better questions, not to copy trades.\n\n## What's in here\n\n| Path | What it is |\n|---|---|\n| `serenity-aleabitoreddit\u002FSKILL.md` | The agent skill: who he is, his edge, the three workflows, risk framing |\n| `serenity-aleabitoreddit\u002Freferences\u002Fmethodology.md` | His framework as ~12 named, transferable principles + a checklist for any new name |\n| `serenity-aleabitoreddit\u002Freferences\u002Ftheses.md` | Per-ticker knowledge base, merged across all periods, grouped by sub-sector, with conviction tiers and how each evolved |\n| `serenity-aleabitoreddit\u002Freferences\u002Farticles.md` | Compact summaries and portfolio-use rules for Serenity's long-form X Articles; full article text is intentionally not stored |\n| `serenity-aleabitoreddit\u002Freferences\u002Ftrack-record.md` | Chronological timeline of his dated calls + an honest calibration note |\n| `serenity-aleabitoreddit\u002Freferences\u002Fmaintenance.md` | Maintenance rules for incrementally distilling new posts into the skill |\n| `serenity-aleabitoreddit\u002Fanalysis\u002F*.md` | The six period analyses the skill was synthesized from (provenance) |\n| `data\u002Faleabitoreddit_tweets.json` | Full tweet archive, all fields (text, metrics, quoted tweets, media, timestamps) |\n| `data\u002Faleabitoreddit_tweets.csv` | Same archive as a spreadsheet (id, url, time, text, likes, views, etc.) |\n| `data\u002Fticker_stats.txt` | His `$ticker` universe by mention count + first\u002Flast seen |\n| `assets\u002Fserenity-avatar.jpg` | Local copy of Serenity's public X avatar used in this README |\n| `prep.py` | Condenses the tweet JSON into monthly chunks and recomputes the ticker stats |\n| `update.py` | Pulls latest tweets, dedupes by id, and refreshes derived data for incremental updates |\n\n## Use it as a skill\n\nOne-command install with [skills.sh](https:\u002F\u002Fskills.sh\u002F):\n\n```bash\nnpx skills add yan-labs\u002Fserenity-aleabitoreddit\n```\n\nOr drop the folder into an agent's skills directory:\n\n```bash\n# Claude Code (project-local)\ncp -r serenity-aleabitoreddit \u003Cyour-project>\u002F.agents\u002Fskills\u002F\nln -s ..\u002F..\u002F.agents\u002Fskills\u002Fserenity-aleabitoreddit \u003Cyour-project>\u002F.claude\u002Fskills\u002Fserenity-aleabitoreddit\n```\n\nIt then triggers on questions about AI\u002Fsemiconductor\u002Foptical\u002Fmemory\u002Fpower\u002F\nneocloud names, supply-chain bottleneck analysis, or evaluating a stock idea.\n\n## His edge, in one line\n\nDon't buy the obvious shovel-seller (NVDA) — trace the supply chain upstream to\nthe single chokepoint a hyperscaler will pay anything to keep flowing\n(optical\u002FCPO, compound-semi substrates, memory, power), where the small market\ncap is most mispriced relative to the trillions flowing downstream.\n\n## Provenance\n\nTweets were collected via `agent-reach` Twitter\u002FX tooling (`twitter-cli`\nhistorically, `xreach` for current incremental updates) using date-windowed\nsearch (full-day windows with intra-day top-up for high-volume days) to work\naround X's pagination\u002Frate limits. X Article bodies were fetched with\nauthenticated article access and distilled into summaries only; full article text\nis not redistributed here. Regenerate the condensed monthly chunks and ticker\nstats from the archive with `python3 prep.py`.\n\n---\n\n*This repository contains only public information about @aleabitoreddit, article\nmetadata, and derived analysis\u002Fsummaries. It is an independent research artifact\nand is not affiliated with, endorsed by, or connected to him.*\n","该项目是一个可安装的Serenity推文档案及AI\u002F半供应链分析技能包。它主要功能包括提供Serenity的原始推文存档、长篇文章摘要、按时间段提炼的内容以及一个可以直接应用于美国股票想法分析的智能代理技能。项目基于5,625条推文（时间范围：2025-07-02至2026-05-30）和4篇X文章构建而成，涵盖了光学\u002FCPO与光子学、InP基板和化合物半导体等多个领域。适合希望深入了解特定行业动态或寻找投资灵感的研究人员和投资者使用，但请注意该工具仅用于辅助决策而非财务建议。",2,"2026-06-11 04:07:55","CREATED_QUERY"]