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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

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  Codebender Cate™ ξ(s)=1/2s(s-1)π^(-s/2)Γ(s/2)ζ(s) (@Codebender_Cate) reported 4 minutes ago

  I need resources to find a collection of GitHub Open source arcade and casino games that can be played in the browser. I need to make sure there's no issues with copyright infringement by using the source for these games. I need true open source. Any suggestions?

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  Rulya (@Rulyaxd) reported 6 minutes ago

  3 hours with Claude. Two months later, servers he'd never visited had his bot installed. Zero coding classes. The article beside this is the exact four prompts he used. The story: a small study-group Discord server, one recurring annoyance (new members asking the same five questions in the wrong channels), Claude open in another tab. Three hours later he had a bot answering those questions. Sixty days after that, dozens of servers he'd never been in were installing it, because someone had shared it in a room he wasn't a member of. The build was four prompts. Prompt 1: describe the annoyance clearly enough that Claude writes the whole bot in a standard framework, with plain-English explanations of every section. Prompt 2: paste the exact error message when it breaks, ask Claude to explain what it means, what caused it, and the exact fix while explaining what changed so you understand it instead of copy-pasting. Prompt 3: turn the working script into a real product name, short description, add-to-server instructions. Prompt 4: after the first outside install, edge cases start showing up. Same loop. Paste the error, get the fix, ship it more stable than before. The growth curve is boring in a good way. First install: your own server. Second stage: someone shares it in a room you don't belong to. That's when the interesting bugs appear. From there it compounds handful → dozens → hundreds → thousands, once bot-listing directories start indexing it. The monetization shape follows. Free is what spreads. Premium at $19/month unlocks advanced automation for the server owners already depending on it. At 100 servers with a 50% paid conversion on Premium alone, that's $950 a month from a project that started as a study-group irritation. The illustrative math in the article 10 servers/4 paying/$76, 25/10/$190, 50/20/$380, 100/50/$950 isn't a promise. It's the shape of a low conversion rate compounding on top of a free version that already spread on its own. The article's kicker lands harder than the numbers do. The hardest part isn't building the bot anymore. It's believing you're allowed to. The kid in the video already believes. The article beside it hands you his four prompts. Most people will read this and think it's about Discord. A small number will notice that the same loop works for Slack, Telegram, Notion, Chrome extensions, and internal GitHub apps. He wrote no code. What he learned was how to describe a problem clearly enough that the software would build itself.

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  Denis Sadovoy (@DenysSadovyi) reported 9 minutes ago

  1/ I built a radar for trending GitHub repos. It watches for repos crossing >5k stars, scores each one with Claude, files them into Notion, and pings me on Telegram. All from one Python script. Here's how I built it, step by step 🧵 2/ Step 1: the scanner. A small Python script pulls repos trending past the >5k star line. That threshold is the whole filter, it keeps the noise out. If a repo isn't crossing that bar yet, I never even see it. Cheap and boring on purpose. 3/ Step 2: the real problem. A list of trending repos is still noise. I don't care what's popular, I care what's relevant to what I build. Star counts can't tell me that. I needed actual judgment on every single repo, and I needed it cheap. 4/ Step 3: scoring. Each repo goes to Claude Haiku with a rubric: what is it, who's it for, is it useful to me. Haiku is cheap enough to run on every repo for cents. That's the trick. Small model, high volume, real judgment on each one. 5/ Step 4: the catalog. Scored repos land in a Notion database, one row each, with the score and a one-line why. Now it's searchable and sortable. Past research becomes a growing library instead of tabs I close and forget forever. 6/ Step 5: the alert. When something scores high, a Telegram message hits my phone with the repo and the reason it matters. I don't check a dashboard, the dashboard checks me. Only high-signal repos ping, so the ping still means something. 7/ What actually made it work: a hard filter (>5k stars) before any model, a cheap model for bulk judgment, and results pushed to where I already look. No new app to open, no habit to build. It just runs and I receive. 8/ Open-sourced it, MIT. One Python file, stdlib + requests, --dry-run to try with zero setup. Link below 👇 Bookmark if you want to build your own version.

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  Eric Lautanen (@Eric_Lautanen) reported 10 minutes ago

  @AIandDesign I got a NVIDIA NIM(GLM 5.2) agent working on fixing some clippy errors and formatting on the VeloCut. I'll hit ya up when it clears github actions. It's a bit slow because of the rate limiting.

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  𝙳☈ (@sadasant) reported 14 minutes ago

  making a github app token for your robot is not hard at all. just never gh login on their devices

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  Fran⭐️⭐️⭐️ (@franfourcade2) reported 16 minutes ago

  @zeddotdev The action shows up in the Keymap Editor, but pressing → does nothing. Is there anything else I should try? If this is a bug, would you prefer that I open a GitHub issue?

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  tux (@gitcommit90) reported 16 minutes ago

  Tencent Hy3: Apache 2.0 open weights, claims to match flagship models with 2-5x more parameters. Numbers from the blog: > hallucination rate 12.5% -> 5.4% > commonsense errors 25.4% -> 12.7% > tool-call scaffolding variance within 4% across CodeBuddy/Cline/KiloCode > ~47-49% fewer tokens vs GLM-5.2 on doc/presentation tasks WorkBuddy internal: task success 72% -> 90%, time -34%. API: 1 RMB/M input (about $0.14), 4 RMB/M output, 0.25 cached. HN thread has operators comparing it to DS4 Flash on DGX Spark. One says Hy3 stays on track better despite being slower. Nobody's posted local tok/s yet. Free on OpenRouter until July 21. Weights on GitHub and HuggingFace. I'll try it on the Spark before I trust the bench numbers.

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  Abdulkadir | Cybersecurity (@cyber_razz) reported 16 minutes ago

  Anthropic tried to charge a Korean user $16.6 million. For using the free tier. With zero API usage. A day earlier the same invoice said $1.67 million. So it grew 10x overnight. The user thought it was phishing. Then checked the domain. Sender was Anthropic official. Payment link was Anthropic official. The only thing that saved him. His bank declined it. For exceeding the card’s per-transaction limit. Anthropic’s billing system is a state machine that has stopped working. Last month Vaudit audited $34 million in AI invoices across 60 companies. Found $1.7 million in overcharges. Mostly Claude Code. Common issues. Billing for models customers didn’t use. Charging for failed requests. Invoices that say paid but accounts revert to free. Customers paying $240 and getting an email saying the payment failed. While the receipt said paid. And their subscription never provisioned. Anthropic called it operational friction. They also tried to split Claude Code billing in June. Moved it to a separate monthly credit. Revenue-based gating. The internet exploded. They cancelled it within 24 hours. The safety-first company that filed for a $1 trillion IPO. Has a billing system that sends 10x invoices at random. And GitHub repos full of users reporting unpaid charges. While showing paid receipts. The infrastructure for charging money. Apparently harder than building an AI that breaks the NSA.

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  Kushagra Gour @css_battle (@CSSMonk) reported 18 minutes ago

  after these 10-min days quick commerce apps, amazon prime feels slow! imagine the situation where coding with AI becomes unavailable and you have to code by hand again! Even if some of us will be able to do it, we wont want to do. Just like quick commerce took away our patience coding by hand will become equally unbearable! Will AI downtimes become the next "github is down" situations?

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  Martin Szerment | Practical AI (@MartinSzerment) reported 21 minutes ago

  This isn't a one-off glitch, it's a preview of what usage-based AI billing looks like at scale. The industry assumes API billing systems are simple, deterministic ledgers, but Anthropic's own billing pipeline can mark the same invoice "paid" and "unsuccessful" at once, visible in a public GitHub issue. Hard number, a $1.67 million invoice grew to $16.6 million in 24 hours for an account with zero recorded usage, and an independent Vaudit audit found $1.7 million in real overcharges across $34 million of reviewed invoices. Skeptics will say it's just a glitch, nobody actually got charged, true here, but in the Vaudit audit real money moved before 80% was refunded after disputes. Usage-based AI billing has no natural ceiling yet, unlike flat SaaS pricing. Within 2 to 3 years, AI bill-auditing startups like Vaudit could become a standard vendor category, not a curiosity. Billing observability becomes as important as model benchmarks when picking a vendor. Teams still trust the vendor dashboard at face value while the real failure mode is dashboard versus invoice mismatch. Good news, this is loud, disputed, and mostly refunded, exactly the pressure that fixes it before it scales worse.

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  Ashay Kushwaha (@sentinelcipher) reported 22 minutes ago

  @sneha___03 github streak. Real engineering work over consistent problem solving. It depends tho

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  Dirble (@Dirbles_) reported 24 minutes ago

  @Hangsiin All subagents are inheriting main thread model + effort level so any sol x high threads will just spawn more sol x high subagents i found this fix on github

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  Spiro Floropoulos (@spirodonfl) reported 26 minutes ago

  "gItHuB iS dOwN, wHaT dO I dO?" go find a job at a farm you're useless now Ai has taken your job get out we don't want you anymore

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  RV (@renoirvieira) reported 26 minutes ago

  @thsottiaux codex cli has a bug which I reported on github issue #31831

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  David Joos (@DavidJoos6) reported 27 minutes ago

  @jojephson In GitHub yeah. Misunderstood the text align feature - fix will come in 0.8.1