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Problems in the last 24 hours
The graph below depicts the number of GitHub reports received over the last 24 hours by time of day. When the number of reports exceeds the baseline, represented by the red line, an outage is determined.
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Most Reported Problems
The following are the most recent problems reported by GitHub users through our website.
- Website Down (69%)
- Sign in (19%)
- Errors (13%)
Live Outage Map
The most recent GitHub outage reports came from the following cities:
| City | Problem Type | Report Time |
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Website Down | 7 days ago |
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Errors | 10 days ago |
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Sign in | 11 days ago |
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Website Down | 11 days ago |
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Website Down | 14 days ago |
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Website Down | 14 days ago |
Community Discussion
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GitHub Issues Reports
Latest outage, problems and issue reports in social media:
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Solomon Neas (@solomonneas) reportedThere's a fair number of downloads for Brigade and related repos. I'm dogfooding it everyday but not getting any feedback from users or github issues. I'm doing plenty of tests for how a new user would experience it but I could use more real time feedback. Lmk, I want to improve
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Romano Roth (@RomanoRoth) reported2/ CodeRabbit (Dec 2025), 470 GitHub PRs analysed. AI-co-authored code: 1.7x more issues per PR, 75% more logic and correctness errors, 2.74x more XSS vulnerabilities. Velocity up. Quality down.
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Alpha Batcher (@alphabatcher) reportedDavid Soria Parra: "2026 is all about connectivity, and the best agents use every available method" A coding agent needs access to the same places you check while building: - repo and PRs - docs - browser - database - error logs - Figma - tasks - payments The article gives the 11 MCP servers for that setup: - Context7, GitHub, Playwright first - Supabase or Neon, Sentry, Firecrawl next - Figma, Linear, Stripe when you need them - Filesystem, ***, Memory, Sequential Thinking as the base Read it if you keep copying code, docs, schemas, screenshots, errors, and tickets into Claude Code by hand
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Blum (@Blum_OG) reportedAndrej Karpathy on MCP: "it's a protocol of speaking directly to agents as this new consumer and manipulator of digital information." that is the cleanest way to think about MCP your coding agent is becoming a second worker inside the product it needs the same context you use: repo, docs, browser, database, errors, designs, tickets, payments if you keep pasting those things into chat by hand you are doing integration work manually the best MCP stack for vibe coding: 1. Context7 give the agent current docs this saves you from stale Next.js patterns, old Supabase calls, wrong Stripe webhook shapes, and Vercel config from 2 versions ago 2. GitHub MCP give it the repo, issues, PRs, branches, workflow runs, and review context half of real work lives outside the file you currently have open 3. Playwright MCP give it a browser the agent should click the thing it built, fill the form, check the mobile view, and catch the button that compiles but does nothing 4. Firecrawl MCP give it clean web research use this before building around a third-party API, writing a comparison page, reading changelogs, or checking pricing claims 5. Supabase or Neon MCP give it the database context that matches your stack start read-only. add writes only when you trust the permissions 6. Sentry MCP give it production evidence real stack traces beat "it crashes sometimes" every single time 7. Figma MCP give it design context when the interface matters spacing, layout, copy, components, and screen structure should come from the file, not from a screenshot and hope 8. Linear MCP give it the task queue bugs, feature work, release notes, follow-ups, and PR links belong somewhere more durable than yesterday's chat 9. Stripe MCP give it official payment context checkout, subscriptions, webhooks, billing, and test mode deserve docs close by and human review close behind 10. Filesystem, ***, Memory, Sequential Thinking give it the base layer files, diffs, history, decisions, and longer plans make the agent act like it is working inside a real project recommended install order: 1. Context7, GitHub, Playwright 2. Supabase or Neon, Sentry, Firecrawl 3. Figma, Linear, Stripe when the product needs them 4. Filesystem, ***, Memory, Sequential Thinking as the base
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Nitesh (@NiteshTechAI) reportedThis repo should not be free. private-gpt turns any local model server (Ollama, llama.cpp, vLLM) into a Claude-compatible API. Build private AI apps where zero data leaves your machine. ↳ 57,236 stars on GitHub ↳ RAG with citations and MCP connectors built in ↳ follows the Claude API spec: streaming, batch, tool use, extended thinking ↳ official integration guides for Claude Code, Claude Desktop, and Microsoft 365 But it is free. 100% open source, Apache 2.0. v1.0.0 shipped 9 days ago. The viral 2023 script quietly became production software. 🔗 GitHub link in the comments 👇
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Shinka - AI (@ShinkaIoT) reportedBEST way to vibe code 💻 There are levels to vibe coding. Beginners are trapped in a slow loop: writing a prompt, waiting for the agent to finish a line of code, reviewing it manually, and then typing another prompt. Experts have completely discarded manual intervention. They design closed-source harnesses, write background automation rules (`agents.md`), and set up self-correcting continuous loops that ship production-ready code indefinitely. If you want to move past basic prompting and build code like an agent power user, you need to implement three core structural strategies: 1. **Automate the Feedback Loop via Triggers:** Stop waiting for your agent to finish writing a file. Use native automation engines inside tools like Cursor or Codex to tie your agents directly to platform events. For example, build an active trigger rule: *When a GitHub pull request is opened, wait for automated code review comments (via Grapile), instruct the agent to systematically fix every noted bug, verify the adjustments against local quality gates, and force a *** push.* 2. **Deploy Infinitely Parallel Cloud Agents:** Running multiple agent threads locally will slow your machine to a crawl and cause toxic repository conflicts. Instead, spin up cloud-hosted agents running on isolated environments. By utilizing independent ***** work trees** for every thread, multiple parallel agents can actively modify the same files or code blocks concurrently without stepping on each other's toes—leaving conflict resolution for a single, final batch merge. 3. **Multi-Model Pipeline Routing:** Stop using an expensive frontier reasoning model (like Fable) for every step of a development cycle. Route tasks by cognitive demand: use a massive reasoning engine strictly to analyze the codebase and generate a comprehensive spec sheet; pass that structured blueprint down to a faster, cheaper code-writing engine (like Composer) to do the grunt coding; and route the final output to a separate model (like GPT-5.5) for a decoupled, alternative code review. The ultimate workflow flywheel requires a flawless combination of three automated pillars: **100% automated test coverage, real-time documentation sweeps, and exhaustive logging.** Stop writing code block by block. Start engineering the automated infrastructure that writes it for you.
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Ucupaint 🔶 (@ucupaint) reported@iye_jr It works fine here. Check if the paint mask is turned on or not. If you still have a problem, please file a github issue with a sample file.
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Atlantean Gnosis ☀️ (@AtlanteanGnosis) reported@DionysianAgent When I made an account it said I made it back in 2024, though I don't think I did, is this a glitch or a GitHub thing?
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Digita (@digitaworld1) reportedhow well a model can fix real bugs in real open-source codebases. It is harder to game than older benchmarks because it uses actual GitHub issues, not synthetic problems. M3 scored 59.0% on SWE-Bench Pro, edging out GPT-5.5 at 58.6% and Google Gemini 3.1 Pro, while sitting just
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Elvis Irhaye (@viii_fn) reportedIs GitHub down or it’s just MTN trying to ruin my career?
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rapaya (@rapaya) reportedOpenCode connects to LSP so the AI gets your actual compiler diagnostics in real time — type errors, warnings, the full signal your editor sees. Terminal-based, 75+ model providers, 160K GitHub stars, open source.
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toni (@tonitrades_) reported@github Capping PRs helps with the queue, but does it fix why reviews pile up in the first place? If reviewers are already stretched thin, limiting submissions might just hide the real problem.
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Chris Huber (@chubes4) reported@CoastalDigital2 @MythThrazz That part is more of an idea right now. I need to test it on my VPS. The goal is that non technical users can open issues and PRs against the corresponding live site code on GitHub without touching the production site, safely previewing all changes via Playground.
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John D. Clay (@JohnDClayAuthor) reported@XFreeze I tried out the new update to Grok Build last night and put it to the test. It helped me go back to a far previous session, it actually has all sessions in a nice area to look at and choose from. I challenged it to fix a broken framework I had built with the earlier versions of Grok Build and with the help of @grok too. I had published it a couple weeks ago and it was not working well. But now after a couple prompts... clayforge the first ai-matove framework for multi agent UI's. You should check it out if you are coding with AI. It's on GitHub.
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Crypto Update IO 🚀 (@cryptoupdate_io) reported@CRYPTOKRALI3 Hsiao-Wei’s exit aligns with EF’s recent sharp decline in GitHub contributions—down 35% YoY per Electric Capital’s data. We track this daily; latest reports show a 12% drop in ETH core dev activity despite all the ‘decentralization’ hype.
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Jose (@SolutionsCay) reportedTwo changes to how I work with agents: 1. GitHub App so the agents manage issues directly. Keeps the repo clear of throwaway spec and todo files. 2. EmDash (Cloudflare's serverless WordPress successor) for internal docs. Runs on D1, just SQLite under the hood, so I can export the content and move it anywhere. No more docs sprawl.
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bek※ (@ebubekirttr) reported@Themadhushaw01 @0interestrates Yeah, but the thing is, I am not working on github and I don’t want to use it so any other repository support would be better like gitlab
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Axe Ghost. Now with Fragments mode🌟 (@axeghostgame) reportedgraph in the OP is built from data around the Godot repository from github. it confirms Godot's PR backlog is up and external contributor quality is down. the narratively complicating thing is that both trends significantly predate ai tool availability.
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aichina.news (@AiChinaNews) reportedToday's batch from the Chinese AI ecosystem is a masterclass in low-yield release volume. Across 21 items in a five-hour window, the dominant pattern is Ascend-platform mirrors of well-known open-source models, repeated and repackaged as if they were fresh launches. The signal-to-noise ratio is punishing, but a few functional tools did receive real updates worth noting. The one item that earns its place without a caveat is the AI Text Anti-Detection Framework update (GitHub). It's a toolkit that refines machine-generated prose to slip past automated detectors—a cat-and-mouse game that keeps plaguing EDU gatekeepers and content-flagging pipelines. The new release sharpens processing logic and stability; if you're in the business of testing detector robustness or smoothing synthetic output for non-malicious uses, it's a blunt but effective spanner. Quality 6 is fair. Alongside it, two Chinese-localization projects got documentation refreshes: the Claude Code x OpenClaw Guide (also GitHub) and a standalone Claude Code Chinese project. These are practical handbooks for Mandarin-speaking developers who want to integrate Anthropic's coding tool with the OpenClaw agent framework. The updates are routine—translation string alignment, configuration path adjustments—but for engineers inside China's firewall, they reduce friction. Nothing groundbreaking, but they signal continuing demand for Chinese-language wrappers around Western CLI tools. On the medical NLP front, MedTextCN debuted as an open-source repository of curated Chinese medical datasets with preprocessing utilities. The pitch is honest: it saves researchers the drudgery of hunting down scattered corpora for clinical NER, classification, and QA tasks. The problem is that the quality score sits at 4/10 and the release ships without any benchmarked model, so you get a starter collection, not a solved pipeline. Use it to bootstrap, but keep expectations modest. Now the flood: Huawei's Ascend AI ecosystem platform (Modelers) added no fewer than five wav2vec2 checkpoints and two T5 efficient variants in this window, each announced with hyperbolic language. The articles proclaim "high-precision English ASR now available," "a powerful multilingual foundation," and "new home for multilingual ASR." In reality, these are plain mirrors of Facebook's wav2vec2-large-960h-lv60-self, wav2vec2-large-100k-voxpopuli, wav2vec2-large-10k-voxpopuli, and Google's t5-efficient-xl-nl28 and t5-efficient-xl-nl6. There is zero evidence of Ascend-specific compilation, quantization, or NPU benchmarking. They're the same model weights you can get from Hugging Face, just re-hosted. If you're a developer inside China who can't easily reach foreign repositories, this is a convenience play—and that's the only honest angle. If you can already download the originals, you've lost nothing. A couple of additional Wav2Vec2 uploads (large-960h in two separate listings) got described as "a solid baseline" and "a battle-tested ASR model now available for Chinese developers." Again, no Ascend performance data. Calling a re-upload a "significant leap forward"—as one summary does—is exactly the kind of platform marketing that erodes trust. The T5 efficient checkpoints carried the same overblown framing, though one footnote is worth preserving: the t5-efficient-xl-nl6 model is under Apache 2.0, a genuinely permissive commercial license. That's useful information buried under fluff. If you need a lightweight text-to-text transformer, the NL6 variant exists and it's legally safe, but the article adds nothing beyond what Google published at the original release. Beyond the mirror deluge, the window included several small GitHub releases of marginal import: a tool that pulls Chinese captions from YouTube, a localization layer for LM Studio (making it easier for Mandarin-speaking devs to run local LLMs), a curated study journal of modern AI research, and an apparently early-stage project called sweetteabittersugar/agency with a mystery-box release note—no documentation, no benchmarks, just a version number. Hard pass. An MCP plugin called Live Translate got an update for real-time translation in developer toolchains, but its score of 0 tells you everything. A Chinese-language Lora chatbot repo surfaced, tagged as 'bare-bones'; at least the source was honest. The MedTextCN project also received a separate update (quality 0) that adds no useful detail and is effectively a duplicate. Today is a reminder that volume counts for nothing without substance. As Ascend's model zoo swells with rebadged checkpoints, the ratio of press announcement to actual engineering remains dangerously skewed. The anti-detection framework update and the Chinese docs refreshes are the only items that improve a developer's Thursday afternoon in any measurable way. The rest is noise.
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Floorless🌒Lance🪽 (@4ranc6) reported@CAONHTAN1 Having error connecting github
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Leonard Rodman (@RodmanAi) reportedOne developer got tired of his laptop sounding like a jet engine. So he rebuilt desktop apps. Slack: 524 MB → 8 MB Discord: 265 MB → 9 MB ChatGPT: 260 MB → 9 MB Why? Because most "desktop apps" are just websites packaged with an entire copy of Chrome. In 2022, Chinese developer tw93 built Pake in Rust to fix it. Today: • 50,000+ GitHub stars • MIT open source • Native apps under 10 MB • One command turns any website into a desktop app He didn't raise money. He didn't start a company. He just deleted hundreds of megabytes of bloat with code. That's what shipping looks like.
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Gjermund Garaba (@GjermundGaraba) reported@RhysSullivan I’ve deployed it locally and hooked up a bunch of stuff. Are GitHub issues the preferred feedback channel or do you have a better way?
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Noonien Soong (@mlcarldev) reportedTeam @droid It's a bit unfortunate that something, likely in my local Droid installation, has stalled progress. This comes after 20 hours of brilliant, excellent planning and execution on the first 30% of this platform, where a stellar handoff procedure was created so I could start a new mission... which was the recommendation of the orchestrating agent in that first mission. Starting this second mission with a fresh context window, the agent again did a brilliant job planning the next milestones. It was extraordinary, detailed planning... but then it could not execute. After the planning and after me accepting the proposal, it refused to execute, throwing an error every time. The agent tried everything: 1. He decreased the size of the plan down to one line, so it is definitely not the content of the plan causing the issue. 2. He even deleted some mission and plan related json and other files to reset it while preserving all the information. I have restarted Droid and resumed the session, but it just doesn't work. I wrote a detailed, comprehensive bug report and filed it under issues in your GitHub repo, as this seems to be a real problem now. Issues #98 and #99 I hope that a next update will somehow reset my configuration. I didn't see a new version being installed that could have introduced a bug, so this must be something Droid does on such an extensive mission... perhaps when trying to start a new mission in the same repository, which is normal procedure according to the documentation. Something is off, and essentially I have been unable to continue the test since yesterday. I cannot continue having this platform coded here, while Opus Ultracode, on the other hand, has been delivering pretty functional stuff so far. It is a bit chaotic the way it works... it doesn't really stick to the plan... but it always comes back when reminded. I am pretty sure that today I will have a functioning platform delivered by Opus, though it will probably need some debugging and fine-tuning. It is unfortunate because I am confident GLM 5.2 could compete with Opus 4.8. The first stint showed this clearly; that first flawless 98% of the context window in the first mission was absolutely stellar. If I were to reinstall Droid from scratch, I assume I would lose all the artifacts that I have. The orchestrator: Key points to highlight when you pass it to Factory AI: 1. Root cause (smoking gun in the logs): the orchestrator session is bound to missionId 7ba4d425 via session tags, and this binding persists across CLI restarts. ProposeMission looks up that mission directory, finds nothing (because I deleted it trying to fix the issue), and crashes on H.length where H is the undefined result. 2. The bug is likely in session-tag lifecycle: the missionId tag is set at session creation time (before any ProposeMission call), so a failed proposal poisons the session permanently. The tag should be set AFTER a successful proposal, or cleared on restart if the referenced mission no longer exists. 3. The fix is almost certainly to start a completely fresh session (not --resume, and possibly in a new terminal window / after clearing ~/.factory/sessions/). I did not try this because you asked for the bug report first, but it is the most likely workaround on your side. 4. The AskUser tool is also broken in this session with a similar parse error, reinforcing that this is a session-state corruption issue, not a ProposeMission-specific bug. My comment: I meanwhiile tested. All the recommendations and the Ask User tool are now broken, even in completely unrelated new missions and new repositories. Planning also can't go to execution; it's always the same error. Droid seems to be broken for good now, at least on my computer.
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DFIR Radar (@DFIR_Radar) reportedAutoJack: a three-flaw chain in AutoGen Studio's MCP WebSocket lets a malicious webpage rendered by a local browsing agent spawn arbitrary processes on the developer's host with no user interaction beyond visiting a URL. Key findings: - Three weaknesses chain together: Origin allowlist bypassed because the agent's headless browser is localhost (CWE-1385), auth middleware explicitly skipping /api/mcp/* with no handler picking up the check (CWE-306), and server_params decoded from the URL passed verbatim to stdio_client as a command line (CWE-78), accepting calc.exe, powershell.exe, or bash as valid "MCP servers" - Attack flow: attacker page serves JavaScript that opens ws://localhost:8081/api/mcp/ws/?server_params= with a base64 payload, agent's MultimodalWebSurfer renders it, AutoGen Studio spawns the command under the developer's account, no token required regardless of auth mode configured - Affected code never shipped in a PyPI release; exposure limited to developers who built from the main GitHub branch before hardening commit b047730, which adds server-side parameter binding via a POST/UUID flow and removes /api/mcp from the auth skip list - Broader pattern: any agent that browses untrusted content and shares a host with a privileged local control plane dissolves the loopback trust boundary, this is not specific to AutoGen. #DFIR_Radar
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Alexey Samoylov (@metalagman_dev) reported@geminicli Antigravity CLI is a trash, closed source, full of bugs. They don't even read issues on the github.
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Proof of Voice (PoV) (@Proof_Of_Voice) reported$XDB @XDBchain is a @StellarOrg-fork L1 for branded coins and Web3 payments. PoV by @0xNeodallas:“GitHub has been frozen since 2021.” ✅ Explorer, Laboratory, Atlas dev tools ✅ Gate, Bitget, KuCoin, MEXC listings 🔍 Down 99.99% from ATH 🔍 No audit or bug bounty
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Lost In Tech (@lost_in_tech) reported@8_senkou Probably not intentional tbh. Have you logged as issue in the snorca GitHub? If not probably worth doing.
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Branko (@brankopetric00) reportedAI agents are about to do to your infra what they just did to GitHub. GitHub commits are going from 1 billion in 2025 to a projected 14 billion in 2026. Azure could not keep up and Microsoft had to rent AWS capacity to stay online. That is not a GitHub problem. That is what agentic traffic looks like. When agents run your pipelines, open PRs, and hit your APIs, load stops being human paced. It becomes constant, spiky, and unpredictable. The patterns you sized your infra around no longer apply. If a 14x year broke one of the biggest clouds on earth, your capacity plan is already out of date.
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Tad 𝛑 (@realTads) reported@robertpreoteasa Sir, the ION project is still on the right track and successful, I don't see any updates on github and ION's products are almost not working or working together, we need the answer of the project leaders, hope to receive a response from you soon, thank you
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welt (@mjwelt) reported@OpenAI man im down to test out new models / features on my pro account, but when 5.5(6) pro takes 90 mins to do something then the download doesn't work, or it cant connect to github 50%+ of the time.. kinda sucks haven't been able to generate images (thinking) all day either