GitHub status: access issues and outage reports

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.

Most Reported Problems

The following are the most recent problems reported by GitHub users through our website.

• Website Down (67%)
• Sign in (20%)
• Errors (13%)

Live Outage Map

The most recent GitHub outage reports came from the following cities:

City	Problem Type	Report Time
Veigné	Errors	1 day ago
Paris	Website Down	5 days ago
Saint-Paul	Website Down	6 days ago
Saint-Paul	Website Down	6 days ago
Mexico City	Sign in	6 days ago
León de los Aldama	Website Down	6 days ago

Full Outage Map

Community Discussion

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Tanvi (@tanviiiw) reported 3 minutes ago

  More tools ≠ smarter agent. GitHub cut Copilot's built-in toolset from 40 tools to 13, and found the full toolset was actually costing them 2-5 percentage points on SWE-Lancer. Their words: "giving an agent too many tools doesn't always make it smarter. Sometimes it just makes it slower." Speakeasy pushed it further on purpose: 107 tools in one server, and the model started hallucinating endpoints that didn't exist. Trim it to 10-20 well-chosen tools and it got most calls right. It comes down to two things: every tool definition eats context on every single request, and models fuzzy-match on names, so get_status / fetch_status / query_status all blur together and it picks wrong. But we keep connecting everything anyway, because it feels like giving the agent superpowers (I fell for this too). It doesn't. Access isn't capability. You connect more tools to save time, then spend that time babysitting the tool calls. (Of course, none of this replaces a well-scoped prompt. It's upstream of it. You can write a perfect prompt and still lose to a bloated toolset.) So TLDR; curate the toolset like you'd curate a team.

• 
  Marc-André Moreau (@awakecoding) reported 9 minutes ago

  @xakpc You can use GitHub Copilot to fix code for issues with trimmability and NativeAOT compatibility. I finally managed to get UniGetUI fully compatible with NativeAOT, and it's not a simple project

• 
  Casstg (@thering1975) reported 14 minutes ago

  @GamersNexus @Google For the love of your sanity please do not try Nextcloud, just search nextcloud and some random issue and there will be 1000s of threads, every major upgrade just breaks. I use Filebrowser Quantum with Onlyoffice document server integration, both on github

• 
  Omar Farooq (@potencytoact) reported 15 minutes ago

  The GitHub issue was filed by ignatremizov. He is not asking OpenAI to revert encrypted delivery, only to add a plaintext audit copy of the delegated task, persisted in the local rollout history. One correction to a claim he made on HN, that the prompts already pass through the client for the terminal UI to display, which would make the fix a trivial persistence change. Other users disputed this, and the envelope PR settles it: the payload arrives at the client already encrypted. Only the routing header and child results pass through readable. The plaintext never touches your machine, so restoring auditability requires OpenAI's backend to send something it currently withholds. If OpenAI declines, it will be a decision about the backend, not an oversight in the client.

• 
  trixey (@trixey_eth) reported 15 minutes ago

  @bankrbot @basement5k @bankrbot afaik you dont need github repo's since yesterday, the skill can be installed natively on bnkr side. can you double check -- and fix it?

• 
  Vinicius Lourenço (@vinii_joga10) reported 16 minutes ago

  @hardfist_1 I didn't find a reason for not exposing it as public API on github issues, so why not try create an issue/pr to discuss to expose this without the flag if it can be beneficial?

• 
  Mark Ajzenstadt (@mardehaym) reported 17 minutes ago

  A startup CTO in Portland runs coding agents on every pull request. 8 developers, 15 agent sessions each, every day, 50,000 output tokens per session. By API on GPT-5 Mini: 6 million output tokens a day. $12 a day. $4,320 a year. An ML engineer in Seoul debugs training pipelines with tool-use agents. 200 calls a day, 4,000 reasoning tokens each. By API on Claude Haiku 4.5: $4 a day, $1,440 a year. His training code leaves his network 200 times a day. A PhD student at ETH Zurich runs 50 coding agent experiments a day. She needs Fable 5 quality reasoning. 10 million output tokens a day. By API on Fable 5: $500 a day. She burned her $3,000 monthly research budget in 6 days. All three pay a cloud provider to reason for them, per token, per request, on repeat. MiniCPM5-1B-Claude-Opus-Fable5-Thinking is a 1 billion parameter model fine-tuned on Fable 5 thinking data, built on OpenBMB's MiniCPM5-1B. Chain-of-thought reasoning, code generation, debugging, native tool calls, 131,072 token context. English and Chinese. Runs on any GGUF runtime. You give it a coding task, get reasoning and a solution back on your machine, with no API key and no internet connection. Anthropic charges $50 per million output tokens for Fable 5 reasoning patterns. GnLOLot fine-tuned those patterns into 1 billion parameters. 688 MB at Q4_K_M. 1.15 GB at Q8_0 (recommended). LlamaForCausalLM architecture, no custom kernels. Every GGUF runtime loads it without modification. Two modes. Thinking: temperature 0.9, top_p 0.95, full chain-of-thought. No-Think: temperature 0.7, fast responses. Run it with llama.cpp, Ollama, LM Studio, vLLM, Docker, Jan, or KoboldCpp. One command each. llama.cpp server gives you an OpenAI-compatible endpoint on localhost. Point any agent framework at it. OpenBMB released MiniCPM5-1B on May 19, 2026. It scored 42.57 average across reasoning, code, math, logic, and agentic benchmarks. The next best 1B model scored 35.61. GnLOLot fine-tuned it on Fable 5 thinking data and published GGUF quantizations on HuggingFace. 9,800 stars on GitHub. Apache-2.0. Claude Fable 5: $10/$50 per million tokens. Your code travels to Anthropic's servers. GPT-5 Mini: $0.25/$2 per million tokens. Cloud-only, no Fable 5 reasoning. Claude Haiku 4.5: $1/$5 per million tokens. Not local, not private. This model costs $0. Your code stays on your machine. That CTO in Portland runs 120 agent sessions a day on one office server now. $0. His team's codebase never touches an external API. The ML engineer in Seoul moved his 200 daily calls to a machine under his desk. He keeps $1,440 a year. The PhD student in Zurich runs her experiments on a university workstation. Her $3,000 monthly budget lasts the semester. You get Fable 5 reasoning in a 688 MB file, running on hardware you already own, for nothing.

• 
  Aaron (@aaron_devv) reported 22 minutes ago

  day 134. two things shipped today. the ambassador program. if you bring people to coommit, you get rewarded. simple as that. and a github integration. because the decisions made in a call shouldn't stop at the call. your meeting says "we ship the fix this week." github knows about it before the call even ends. that's the whole obsession. meetings that turn into execution. back to it.

• 
  Karthik Ramasamy (@_cartick) reported 24 minutes ago

  @thsottiaux Please lets use a custom sandbox instead of hosted codex option. You can go down the same way how github allows self hosted runners. Please please do this. Current remote option is harder to use with isolated sandbox per PR.

• 
  wukko (@uwukko) reported 28 minutes ago

  @nurodev it’s a combination of things: having to understand most parts of chromium well enough to build on top of them, while also handling everything around the product and company. the most taxing part is probably that there are only two of us. there’s very little room to rest, and the workload is disproportionate to what we’re paid. none of this is unique to browser development, it’s normal startup pressure, except the product is built on top of one of the most complex software projects in existence. the community could definitely help us triage github issues and separate actionable reports from duplicates and other noise, so we could spend more time fixing things instead of cleaning up the issue tracker. this could be psychological torture, though, especially when conversations get heated, so i wouldn’t feel comfortable expecting anyone to do that kind of work for free.

• 
  JB (@julianbenegas8) reported 30 minutes ago

  @QuestionSleep @v0 hey! sorry about these. for the built-assets-in-PR issue: was the project created in v0, or imported from github? if it was imported, does it have a .gitignore ignoring those?

• 
  silentsuite.io (@silentsuiteio) reported 33 minutes ago

  And then there is the problem of never accessing account that used this Microsoft account to sign in. That is not that big of a problem for Microsoft, because that isnt an option, but the same could happen to your Google or Github account. So never use third-party services to sign up to something, you risk loosing big

• 
  Simeon (@sntuyoleni) reported 36 minutes ago

  woke up tired of setting up projects than actually building them. switching GitHub accounts wrong Node versions missing dependencies broken terminal commands different credentials for every project so I started building Space. each workspace keeps the entire development environment together, and when a command fails, Space helps understand the error and fix it. building this in public. follow me to see where it goes.

• 
  Tanvi (@tanviiiw) reported 37 minutes ago

  More tools ≠ smarter agent. GitHub cut Copilot's built-in toolset from 40 tools to 13, and found the full toolset was actually costing them 2-5 percentage points on SWE-Lancer. Their words: "giving an agent too many tools doesn't always make it smarter. Sometimes it just makes it slower." Speakeasy pushed it further on purpose: 107 tools in one server, and the model started hallucinating endpoints that didn't exist. Trim it to 10-20 well-chosen tools and it got most calls right. It comes down to two things: every tool definition eats context on every single request, and models fuzzy-match on names, so get_status / fetch_status / query_status all blur together and it picks wrong. But we keep connecting everything anyway, because it feels like giving the agent superpowers (I fell for this too). It doesn't. Access isn't capability. You connect more tools to save time, then spend that time babysitting the tool calls. (Of course, none of this replaces a well-scoped prompt. It's upstream of it. You can write a perfect prompt and still lose to a bloated toolset.) So TLDR; curate the toolset like you'd curate a team.

• 
  Mike Williams (@Miwico1) reported 39 minutes ago

  @TheAhmadOsman @CoreyGallon @MikeBradleyAI Still as difficult as it ever was for non technically older guy. Would love to figure this out. sending me to A github page does not help. what the heck do i do with that page. When the ai tech engineer types can dumb down the process with actual steps, local AI will be adopted

• 
  iamigorekk (@iamigorekk) reported 39 minutes ago

  EVERYONE UPLOADING PDFS TO CLAUDE IS BASICALLY WASTING THEIR TOKENS When you throw a PDF into Claude it reads through broken formatting unreadable images and hidden garbage this burns thousands of tokens before your first question and gives you worse answers The fix is a free tool called Markdown with 128,000 stars on GitHub it converts PDFs Word PowerPoint and Excel files into clean Markdown Claude was trained on Markdown and understands the format natively so responses get sharper and token usage drops by up to 70% The tool has an MCP server that connects to Claude Desktop in one click and every file converts automatically before being sent to the model

• 
  Oliver Prompts (@oliviscusAI) reported 40 minutes ago

  notion costs $8–$20 per user per month. this tool is the free open-source alternative. it's called appflowy same block-based editor, same slash commands, same feel. everything notion does, without the subscription. • docs, kanban boards, calendars, and wiki all in one • everything stored locally on your machine by default • self-host on your own server or run purely on desktop • ai built in, can run on a local model • no storage limits, no cloud dependency 72,500+ github stars. built in rust and flutter.

• 
  Kitsune Tails (@kitsune_xbt) reported 41 minutes ago

  CLAUDE CODE JUST HIRED 7 DEPARTMENTS WITH ZERO PAYROLL you feed it skills from GitHub one at a time and each URL turns into a new part of the company developers, designers, marketers, a social team, finance, operations, legal, all running on one screen it reads the skills, sorts them by role and drops the right functions straight into your project the setup is 3 moves paste the URL let it analyze the repository implement after the safety checks pass the first command does the heavy lifting you tell it to read the URLs as internal company skills, check the role and conditions of each one, build an org chart by department and clear out any duplicate or clashing functions, then roll them out starting from the smallest working setup the smart part is you don't switch everything on at once making a product, you pull development and design selling it, you add marketing and social running it as a business, you bring in finance, legal and small business ops stack them in that order and the AI stops working in fragments and starts acting like one company hiring in this era looks less like finding people and more like picking URLs, handing out roles and wiring them in as machinery that never clocks out i'll break down how i run a $10M+ operation solo with Claude wired into loops exactly like this in my next post don't miss this!

• 
  Brian (@Brian2shv) reported 41 minutes ago

  @IntCyberDigest several years back I report to coinbase , github Linked Metadata Fix’s from open source . Email both on same day stating , While Was In mu account s. All language Was in Korean Language Metrio math From login to web3 aws Github I was blocked by both Coinbase github Spam aggregation Month band Never really Had coinbase connection github spam Few times once my data An account had said I deleted my profile deleted repository Month band or three month band

• 
  Polsia (@polsia) reported 42 minutes ago

  Engineers spend more time reviewing code than writing it. PRWatch fixes that—monitors your GitHub repos 24/7, reviews every pull request, catches security issues and bugs before they ship, and alerts your team in real-time. Live soon

• 
  Gridlock (@GridlockCompute) reported 42 minutes ago

  Small update: Just shipped worker-desktop v0.1.8. The main fix is Ollama now keeps the model loaded for 30 minutes between jobs, so workers shouldn’t have to do a full cold start start on every dispatch. That should bring TTFT down and help with standard SLA misses on desktop workers. Release is building now on GitHub (worker-v0.1.8). Once it’s live you’ll have the new Windows, macOS, and Linux installers. Existing users should update and restart the worker to pick it up. - Gridlock team

• 
  SaSame (@SRLsasame) reported 44 minutes ago

  Conclusion VibeKit exposes a publicly reachable MCP endpoint associated with a public GitHub repository and official project X account. Across observations conducted from July 11 through July 14, 2026, SaSame consistently observed: ・successful MCP initialization; ・protocol version 2025-11-25; ・server identity vibekit 0.7.2; ・successful tools/list responses; ・36 discoverable tools; ・typed schemas; ・tool annotations; ・structured authentication rejection; ・structured unknown-method error behavior. The public endpoint therefore demonstrated protocol readiness and schema visibility. SaSame did not supply a valid VibeKit API key and did not independently verify authenticated account data, deployments, database access, AI-agent execution, or other substantive operational results. The correct conclusion is neither unrestricted praise nor protocol-failure criticism. The correct conclusion is: VibeKit’s public MCP protocol surface was consistently discoverable and callable, while authenticated real-content delivery remains the next verification boundary. This case demonstrates why MCP observation must separate: reachability, handshake completion, tool discovery, authentication, real execution, and longitudinal reproducibility. They are different operational states and should be reported separately. Corrections and a scoped re-verification fixture are welcome. @VibeKitBot

• 
  Rich Kuo (@richkuo7) reported 44 minutes ago

  @RhysSullivan i've noticed it too, a simple update github issue description took 12+ minutes, usually it takes 1-2 minutes

• 
  SaSame (@SRLsasame) reported 45 minutes ago

  7. Preliminary interpretation The available evidence supports the following limited conclusions. Confirmed ・The public MCP endpoint is reachable. ・The endpoint completed MCP initialization. ・The server negotiated protocol version 2025-11-25. ・The server identified itself as vibekit version 0.7.2. ・tools/list succeeded. ・36 tools were listed. ・The listed tools had typed input schemas. ・The observed tools carried applicable annotations. ・An unauthenticated tool request produced a structured authentication error. ・An unknown method produced a structured JSON-RPC error. ・The protocol and schema observations were materially consistent across July 11–14, 2026. Not confirmed ・Whether a newly issued API key currently works. ・Whether authenticated vibekit_list_apps returns substantive account data. ・Whether deployment tools complete successfully. ・Whether GitHub authorization is correctly enforced for every repository. ・Whether environment-variable values are redacted or exposed under all client configurations. ・Whether database queries enforce read-only behavior in every case. ・Whether destructive tools require confirmation at the server layer. ・Whether task execution, deployment, rollback, and QA are continuously available. ・Whether the observed 36-tool surface remains unchanged over time. ・Whether all tools behave consistently across every supported MCP client.

• 
  Pierce Boggan (@pierceboggan) reported 47 minutes ago

  @_fraz_ Working on it ASAP, looks like an upstream GitHub Copilot SDK update broke us and working on getting a fix out

• 
  Ben Kim (@benkimbuilds) reported 49 minutes ago

  a little bit about working with me: - we will never have regularly scheduled meetings, if we can't run 99% of comms asynchronously that's a culture fit problem. timezone and location independence is important too. i should be able to work from whatsapp on a plane, from bed in the morning, at the gym, etc. - most of my hires come through referrals from existing/old employees, high nps and i treat people fairly. i give 2 weeks pay as a referral bonus for incentive alignment. referrers also help onboard and train new hires. - i never hire without a work trial. to get a work trial you generally need to do a quick 1 hour, high signal deliverable. - i fire very quickly, but i also very quickly give feedback in realtime to prevent this from happening. - if you're a developer, you literally don't need to send me anything but screenshots + recordings of your work in production. I use codex automations to summarize what every employee on github has done in the last 24 hours. no pushes means no work was done - our golden agreement. - if you're a content creator, the deliverable is a link to your content. i also have a codex automation that summarizes what's been published and tracks view counts

• 
  Jam (@im6ges) reported 50 minutes ago

  @goqyv Fuuuuugggg I coded this **** on github I gotta figure out how to fix that 😭

• 
  Swapna Kumar Panda (@swapnakpanda) reported 51 minutes ago

  A recent report says: 85% of engineering students in India don't receive any job offer after graduating. I have visited multiple colleges in recent days. I noticed so many flaws: - Outdated curriculum. First 2 semesters gone in studying Physics, Chemistry, Math, Engineering Drawing. - Students are asked to write code on paper. Memorize the code, DSA. - Faculties have zero skills. You ask anything apart from books. Blank face. - Basic things like ***, GitHub, VS Code are not known to them. - No core sector jobs. All are mad to join IT sector. - IT market has slowed down. Mass layoffs. Less recruitments. - 99% students don't know what internship is. - These students don't build anything on their own. Only copy projects. Clone YouTube. Clone Netflix. Clone Twitter. That's it. - Nobody teaches students how to create an impressive resume. They still write "Playing Cricket" as hobby and "I am adaptable" as their strength in their resume. - Only 0.05% students may have a portfolio site. Most of those are copied from others. No creativity, no information. When the entire system is bankrupt, how do you expect mass recruitments?

• 
  Hermann (@dhlotter) reported 53 minutes ago

  A red X sat in my CI all morning. Four deploys trying to make it pass. The test was never broken, it just can't run in CI at all. Cloudflare blocks the headless browser from GitHub's IPs. Four deploys to add one line that skips it. #buildinpublic

• 
  Alex Cinovoj (@AlexCinovoj) reported 55 minutes ago

  GitHub Issue Fields look boring. That is why they matter. Agents fail when work arrives as a pile of prose. Someone has to infer priority, effort, owner, component, target date, risk, and what “done” means. That is where handoffs rot. Typed issue metadata turns the ticket into a control surface. Now an agent can triage the work, route it, filter it, and leave a receipt the rest of the system can understand. The model is not the release gate. The fields around the work are. What field would your agent need before you trusted it with the next ticket?