标签：#github

GitHub热门项目 | b站会员购购票辅助工具 | Stars: 3,685 | 164 stars today | 语言: Python

GitHub热门项目 | An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours. | Stars: 72,256 | 415 stars today | 语言: Python

After spending two weeks debugging issues that only showed up in production — a sitemap _redirects rule that was blocking my own sitemap-index.xml and a Bluesky image upload race against Cloudflare Pages deploy lag — I added three post-deploy checks to my workflow. They're fast and specific to the failure modes I've actually hit, not a full end-to-end test suite. Three sites (aiappdex.com, findindiegame.com, ossfind.com) on Cloudflare Pages with Astro 5 SSG. Here's what I check. Check 1: Sitemap reachability The simplest check and the one I should have had from day one. After a Cloudflare Pages deploy, I verify that sitemap-index.xml is reachable and returning 200 on all three domains: for domain in aiappdex.com findindiegame.com ossfind.com ; do status = $( curl -s -o /dev/null -w "%{http_code}" "https:// $domain /sitemap-index.xml" ) echo " $domain /sitemap-index.xml → $status " if [ " $status " != "200" ] ; then echo "FAIL: $domain sitemap unreachable" fi done I also check sitemap-0.xml — the actual URL sub-sitemap that @astrojs/sitemap generates — and assert that it contains at least a minimum expected URL count. For aiappdex.com that threshold is 1,000; if it drops below that after a deploy, the ETL data pipeline probably broke silently. The reason this check exists: I had a _redirects rule rewriting sitemap-index.xml → sitemap-0.xml as an emergency workaround that turned out to be wrong. It was live for five days before I found it. The rule was blocking the real sitemap-index.xml from reaching crawlers while appearing fine in the browser (which followed the redirect). Curl with -o /dev/null -w "%{http_code}" doesn't follow redirects by default, so it would have caught this immediately. Check 2: IndexNow batch submission After every successful sitemap check, I run node scripts/indexnow.mjs . The script reads the live sitemap XML from each domain, collects all URLs, and POSTs them to the IndexNow endpoint for Bing, Yandex, Naver, and Seznam using site-specific k

After spending two weeks debugging issues that only showed up in production — a sitemap _redirects rule that was blocking my own sitemap-index.xml and a Bluesky image upload race against Cloudflare Pages deploy lag — I added three post-deploy checks to my workflow. They're fast and specific to the failure modes I've actually hit, not a full end-to-end test suite. Three sites (aiappdex.com, findindiegame.com, ossfind.com) on Cloudflare Pages with Astro 5 SSG. Here's what I check. Check 1: Sitemap reachability The simplest check and the one I should have had from day one. After a Cloudflare Pages deploy, I verify that sitemap-index.xml is reachable and returning 200 on all three domains: for domain in aiappdex.com findindiegame.com ossfind.com ; do status = $( curl -s -o /dev/null -w "%{http_code}" "https:// $domain /sitemap-index.xml" ) echo " $domain /sitemap-index.xml → $status " if [ " $status " != "200" ] ; then echo "FAIL: $domain sitemap unreachable" fi done I also check sitemap-0.xml — the actual URL sub-sitemap that @astrojs/sitemap generates — and assert that it contains at least a minimum expected URL count. For aiappdex.com that threshold is 1,000; if it drops below that after a deploy, the ETL data pipeline probably broke silently. The reason this check exists: I had a _redirects rule rewriting sitemap-index.xml → sitemap-0.xml as an emergency workaround that turned out to be wrong. It was live for five days before I found it. The rule was blocking the real sitemap-index.xml from reaching crawlers while appearing fine in the browser (which followed the redirect). Curl with -o /dev/null -w "%{http_code}" doesn't follow redirects by default, so it would have caught this immediately. Check 2: IndexNow batch submission After every successful sitemap check, I run node scripts/indexnow.mjs . The script reads the live sitemap XML from each domain, collects all URLs, and POSTs them to the IndexNow endpoint for Bing, Yandex, Naver, and Seznam using site-specific k

Pernahkah kamu membuat sebuah proyek perangkat lunak, mengunggahnya ke GitHub, lalu menyadari bahwa kamu belum menambahkan lisensi apa pun di repositori tersebut? Banyak developer pemula yang mengira bahwa menaruh kode di GitHub otomatis membuatnya menjadi open-source . Padahal, secara default , proyek tanpa fail lisensi memiliki hak cipta yang tertutup ( exclusive copyright ). Artinya, orang lain atau developer penerus secara teknis tidak boleh menyalin, mendistribusikan, atau memodifikasi kodemu. Agar proyek tersebut aman untuk dilanjutkan dan dimodifikasi oleh pengembang selanjutnya, kita wajib menambahkan lisensi terbuka. MIT License adalah pilihan paling aman dan populer karena sifatnya yang sangat membebaskan. Berikut adalah cara kilat menyematkan MIT License pada repositori GitHub yang sudah telanjur berjalan tanpa perlu menggunakan command line : Langkah 1: Buat Fail Baru di Repositori Buka halaman utama repositori GitHub kamu. Di bagian atas daftar fail dan folder kodemu, klik tombol Add file , kemudian pilih Create new file . Langkah 2: Pancing Fitur "License Template" Pada kolom pengisian nama fail, ketikkan kata LICENSE (pastikan menggunakan huruf kapital semua). Begitu kamu selesai mengetikkan kata tersebut, GitHub akan otomatis memunculkan sebuah tombol baru di sebelah kanan bernama Choose a license template . Klik tombol tersebut. Langkah 3: Pilih MIT License Kamu akan dibawa ke halaman yang berisi daftar berbagai jenis lisensi open-source . Pilih MIT License dari menu di sebelah kiri. GitHub akan otomatis meracik draf teks lisensinya, lengkap dengan nama akun GitHub kamu dan tahun saat ini. Klik tombol hijau Review and submit di pojok kanan atas. Langkah 4: Lakukan Commit Gulir ke bagian bawah halaman. Tulis pesan commit yang singkat dan jelas (misalnya: "Add MIT License for future development" ), lalu klik tombol hijau Commit changes... . Selesai! Sekarang proyek lama kamu sudah memiliki "payung" yang jelas dan resmi berstatus open-source . Reposito

GitHub added a tiny field to the Copilot usage metrics API this week that is going to create a lot of very confident spreadsheets. Enterprise and organization admins can now see ai_credits_used in the user-level Copilot usage reports. One field. Per user. Available for single-day and 28-day reports. It is not the invoice, and GitHub is careful to say it is a consumption signal rather than a billed total. Still, the shape is obvious. Now AI usage can sit next to adoption, activity, team, department, cost center, and whatever else the company already exports into a dashboard. That is useful. It is also exactly how a tool metric becomes a management metric. And once that happens, the question is no longer "can we measure AI usage?" The question is "what weird behavior will this metric create?" every useful metric becomes a temptation I understand why this field exists. If a company is paying for Copilot, especially with usage-based pieces attached to more expensive models and premium features, it needs some way to understand consumption. Platform teams need budget signals. Engineering leaders need adoption signals. Procurement needs something more concrete than "people seem to like it." Finance will eventually ask why one org burns through credits much faster than another. That is normal. The problem starts when a consumption signal is treated as a productivity signal. High AI credit usage might mean a developer is doing valuable work with agent mode, code review, test generation, refactoring, or research. It might also mean the developer is stuck, repeatedly asking the model to solve the wrong problem, generating code that gets deleted, or using a heavyweight model where a small one would have been fine. Low AI credit usage might mean a developer does not need much help. It might mean the work is mostly design, review, debugging, incident response, mentoring, or architecture. It might mean the codebase is small and well understood. It might mean the developer is skept

The problem GitHub shows your pull requests in whatever order they happened to be opened — not in the order they actually need your attention. A one-line typo fix and a PR touching authentication code get exactly the same visual weight in your inbox. Multiply that across a dozen open PRs and you spend more time deciding what to look at than actually reviewing. What I built PR Focus is a Chrome extension (Manifest V3) that sits on top of GitHub's PR pages. It combines three signals into a single priority queue: CI status — failing checks bubble up PR age — stale PRs don't get forgotten AI risk score (0–100) — weighted toward changes touching auth, database, or infra code Each PR also gets a plain-English summary generated from the actual diff (not the title someone wrote at 11pm), and you can generate an approve / request-changes draft review in one click, edit it, and send — without leaving the extension. Why BYOK instead of my own AI backend This was the decision I spent the most time on. Running my own AI backend would have meant: A server in the data path of every PR diff users review — a much bigger trust ask, especially for private repos. Either eating the AI cost myself (unsustainable as a solo dev) or marking it up into a subscription. Going BYOK (bring your own key — OpenAI, Groq, Mistral, or a local Ollama instance) flips both of those: Your GitHub token and AI key live in chrome.storage.local . There's no server of mine in the path — PR diffs only ever go to the AI provider you explicitly configure. Groq's free tier is generous enough to run the AI features for free for most individual workflows. You're paying provider cost directly, with zero markup, if you pay anything at all. How it's built Manifest V3 — required rethinking persistence patterns that worked under MV2's persistent background page; service worker lifecycle and content script injection needed more careful handling. GitHub REST + GraphQL APIs rather than DOM scraping — more upfront work, but

GitHub热门项目 | 开箱即用的AI标书编写工具，标书AI生成工具，投标工具箱、知识库、标书查重、废标项检查，完全开源免费，欢迎使用 | Stars: 941 | 129 stars this week | 语言: JavaScript

GitHub热门项目 | An extremely fast Python package and project manager, written in Rust. | Stars: 86,594 | 33 stars today | 语言: Rust

GitHub热门项目 | A design system built by IBM | Stars: 9,194 | 6 stars today | 语言: TypeScript

GitHub热门项目 | Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations. | Stars: 193,297 | 135 stars today | 语言: TypeScript

GitHub热门项目 | omo/lazycodex: The coding agent for tokenmaxxers;the one and only agent harness for complex codebases. For your Codex, for your OpenCode | Stars: 63,007 | 228 stars today | 语言: TypeScript

GitHub热门项目 | The open-source AI voice studio. Clone, dictate, create. | Stars: 30,772 | 140 stars today | 语言: TypeScript

GitHub热门项目 | CIPP is a M365 multitenant management solution | Stars: 1,186 | 2 stars today | 语言: JavaScript

GitHub热门项目 | | Stars: 1,204 | 2 stars today | 语言: JavaScript

GitHub热门项目 | ToolJet is the open-source foundation of ToolJet AI - the enterprise app generation platform for building internal tools, dashboard, business applications, workflows and AI agents 🚀 | Stars: 38,040 | 5 stars today | 语言: JavaScript

GitHub热门项目 | Unsloth Studio is a web UI for training and running open models like Gemma 4, Qwen3.6, DeepSeek, gpt-oss locally. | Stars: 66,943 | 116 stars today | 语言: Python

GitHub热门项目 | An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines. | Stars: 9,302 | 421 stars today | 语言: Python

GitHub热门项目 | A feature-rich command-line audio/video downloader | Stars: 171,966 | 341 stars today | 语言: Python

GitHub热门项目 | Turso is an in-process SQL database, compatible with SQLite. | Stars: 20,044 | 774 stars today | 语言: Rust