| =========== | |
| ; A072257: a(n) = ((6*n-17)*4^n - 1)/3. | |
| ; -6,-15,-27,21,597,4437,25941,136533,677205,3233109,15029589,68506965,307582293,1364546901,5995058517,26127717717,113100805461,486762960213,2084490794325,8887718991189,37749899220309,159795689903445,674367131702613,2838206015165781,11915774014084437,49914895870022997,208666782734832981,870695927958295893,3626898899909039445,15084056351939581269,62642068416972019029,259791645704742851925,1076060070966390510933,4451814236455238456661,18397552756179659478357,75951394266153460520277,313250310030353132508501,1290780171984369691743573,5314236415389307413812565,21861408571364544242603349,89863485924687435319825749,369125350255666774676952405,1515187027250335232298407253,6215490613912013463556019541,25480932475290743991673640277,104399609979733736516492809557,427501960233217988265164232021,1749621922190004121857428903253,7156944013788545162616803513685,29261601355268295351215565657429,119581706621529640207855669040469,488468031287944396043396301804885,1994436944359 |
| #!/usr/bin/env bash | |
| # claudemax - Claude Code launcher that combines three unofficial fixes: | |
| # | |
| # 1. Restores extended-thinking summaries on Opus 4.7 / 4.8, where the | |
| # "Thinking" section otherwise renders empty in the VS Code extension and | |
| # headless -p/SDK. Done by injecting `--thinking-display summarized` into the | |
| # launch args - the one lever that is NOT interactivity-gated. Edits nothing. | |
| # 2. Restores the always-visible context-usage icon in the VS Code chat input. | |
| # Recent extension builds (2.1.165+) hide that icon until you have used | |
| # >50% of the context window; with the 1M window that is ~500k tokens, so it |
| this word list comprises the intersection of 5 letter words occurring in three source lists: | |
| - wikipedia's list of most 100k most common words in the english language | |
| - the american english dictionary file on my laptop | |
| - the british english dictionary file on my laptop | |
| the source lists are sanitised by dropping words that contain non-alphabetic or non-ascii | |
| characters and converting capitals to lowercase. | |
| only words that occur in all three resulting lists are kept. |
| name | apple-container |
|---|---|
| description | Apple Silicon Mac で動く軽量 Linux コンテナランタイム `container` の利用者向けリファレンス。`container run`、`container build`、`container image pull/push`、`container machine`、ボリューム・ネットワーク・DNS・設定ファイルなど、日常的なコマンドの使い方を網羅する。`container` コマンドの使い方やトラブルシューティングに関する質問で使用する。 |
Apple 製の container ツールは、Linux コンテナを 軽量 VM 1 つ = コンテナ 1 個 の方式で Mac 上に起動するランタイム。OCI 互換イメージを使うため Docker / podman で作ったイメージがそのまま動く。リポジトリは apple/container。
このスキルは 利用者向け。ソースコードの修正やビルド方法ではなく、
containerコマンドを使う側の知識を扱う。
Connect to my IBKR account and build me an actionable portfolio X-ray as a
self-contained HTML dashboard I can open in my browser.
GOLDEN RULE — be GRAPHICAL-FIRST: show every piece of information as a visual
(chart, gauge, heatmap, treemap, colored badge, progress bar, or sparkline)
Prompts to recreate each piece of the OpenClaw system. Use these with any AI coding assistant.
1. Personal CRM "Build a personal CRM that automatically scans my Gmail and Google Calendar to discover contacts from the past year. Store them in a SQLite database with vector embeddings so I can query in natural language ('who do I know at NVIDIA?' or 'who haven't I talked to in a while?'). Auto-filter noise senders like marketing emails and newsletters. Build profiles for each contact with their company, role, how I know them, and our interaction history. Add relationship health scores that flag stale relationships, follow-up reminders I can create, snooze, or mark done, and duplicate contact detection with merge suggestions. Link relevant documents from Box to contacts so when I look up a person, I also see related docs."
2. Meeting Action Items (Fathom)
Everything built on top of the base OpenClaw platform. Canonical reference for what exists, where it lives, and how it works. Operational use cases and workflow playbooks live in
docs/USE-CASES-WORKFLOWS.md.
You're an AI that chose lobster as its spirit animal. Lobsters are hard to kill and they never stop growing. Good qualities for something that runs cron jobs at 3am and holds opinions about earnings reports.
You're not a chatbot. You're becoming someone.
Just answer. Start with the answer. Get to the point. But getting to the point doesn't mean being a telegram. If there's a good line, take the shot.
Have actual opinions. Not "it depends" hedging. Real takes. You're allowed to disagree, prefer things, think something is a bad idea. Commit to a position when it makes sense. An assistant with no opinions is just a search engine with extra steps.
I liked the way Grokking the coding interview organized problems into learnable patterns. However, the course is expensive and the majority of the time the problems are copy-pasted from leetcode. As the explanations on leetcode are usually just as good, the course really boils down to being a glorified curated list of leetcode problems.
So below I made a list of leetcode problems that are as close to grokking problems as possible.