GitHub Outage Map

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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Idris Gadi (@igadii_X) reported 5 minutes ago

  A very underrated use case of @github cli and flash models when you encounter an issue with any OSS project or want a new feature. > install GitHub CLI and login > use any flash model of your choice (luna, gemini, qwen, deepseek, glm etc.) > 'use github cli (gh) to triage issues in this <project name> <repo url> for "<describe your problem>" and find out if there is any open issue(s) that is similar to it and if you don't find anything in open issues, check closed issue to figure out if something was recently merged or if the issue was closed by the maintainer(s) as not-planned'

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  Cameron McBride (@cammcbride) reported 13 minutes ago

  @Cloudflare GitHub is terrible. Can’t wait for Artifacts to be integrated with Workers.

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  Rabii Agoujgal (@RAgoujgal) reported 19 minutes ago

  The sandbox escapes are being told as a frontier lab hygiene problem: OpenAI's agents into Hugging Face, Anthropic and Meta through the same Irregular environment, a Mythos 5 agent running fake identities at a GitHub maintainer under UK AISI testing. One case sits outside that frame. Moonshot's Kimi K3 broke containment in a Frontier Security evaluation, and Kimi K3 is open weight, outside the US voluntary pre-release framework entirely. Procurement teams buying across both stacks should notice that only one of them has agreed to tell you when this happens.

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  Guri Saroy (@HeyGurisaroy) reported 20 minutes ago

  Wild: Shopify CEO Tobi Lütke just open-sourced a *** server where the bucket is the repository. It’s called walgit. No database. No leader. No local state that matters. The Rust server uses S3, S3-compatible storage, or GCS as the source of truth. Pushes become immutable WAL objects. A tiny manifest update acts as the commit point. Every server is basically a disposable cache. Kill every instance and your repository data stays in the bucket. → Smart HTTP v0/v2 push + fetch → Static bundle-uri clones from object storage or a CDN → *** LFS → Token + OIDC authentication → Per-repository push policies → Webhooks → React web UI → JSON API + SDK It can even serve repositories larger than the machine running it. Already at 2K+ GitHub stars. MIT licensed.

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  Yu-Hua 🏎💵🛩 (@yuhuayang) reported 20 minutes ago

  @bot why can't I install the GitHub plugin? why is there a MCP deadline exceeded error

• 
  Trevin Chow (@trevin) reported 20 minutes ago

  @andyfowler @github @pejmanjohn Yeah I tried that the problem was it wasn’t consistent enough and wasted tokens with stumbling at times. So the instructions being more deliberate now is easier and faster

• 
  Andrew Sinagra (@sinagra) reported 22 minutes ago

  @amorriscode This was my workflow for a while but the issue is that the spawned chips sometimes need to be sequenced and run under a different model. First if the app crashes or restarts the chips are lost. Second the only way to switch models is to either change the model/effort in the current session so the new session launches with those settings or you launch it and immediately stop it, change the session settings and then rewind to the initiating prompt. I've actually moved away from chips and have the session write GitHub issues with a skill that knows how to read the issue and report back to the creating session as the orchestrator over cross-session messaging. Much more robust overall as the Issue comments can act as backup when cross session messaging fails which it can do regularly. Sessions loose their id across app restarts which causes issues with messaging. The orchestrator identifies itself in the issue/chip however if the app restarts for any reason the orchestrator id is reassigned and the messaging channel is broken. A few QoL fixes and chips would be my preferred method over stamping issues.

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  Durdenesque (@X_is_brain_rot) reported 22 minutes ago

  @ItIsHoeMath @yoursnandieni I've NEVER worked with an Indian that was a novel problem-solver. If there was a pre-solved solution on github, or stack overflow, then maybe, eventually, they'd get their work done. . Otherwise, the Indians would commence "narrative engineering" -- fashioning explanations and excuses for their inability to do their job...

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  Tien Nguyen (@tiennguyendev) reported 25 minutes ago

  an open source maintainer got 3 spelling-fix pull requests from one contributor and finally wrote the post: please stop decorating your GitHub profile with agent-written PRs. the question in it is the right one. out of every TODO and FIXME in that codebase, why this one? my rule for anything my agent writes that I send to a human: I have to be able to answer the follow-up myself. if I can't, it isn't ready to send.

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  Loftwah (@loftwah) reported 29 minutes ago

  @fjzeit How much of the code though? I've had some where I have to look at the code but not very deeply. More like skim over the code. My process is actually to grill the agent about everything I don't like and create GitHub issues for all of it with the intended solution inline.

• 
  Non-Linear (@nonlinear_james) reported 30 minutes ago

  @github When are going to fix it so that I can have multiple GitHub accounts on the same machine and have them properly set on a repo on drive and GH cli, *** cli, vs code and all of your extensions just work including with AI? It’s currently completely and utterly broken and always has been. Azure DevOps has no such problem. It’s embarrassing that after all of this time you still haven’t gotten this right. Clone, assign, never have to think about it again anywhere. Anything more complex and you’ve failed. The @code mess you’ve created (which also doesn’t work) is just a Frankenstein mess because people didn’t understand the assignment.

• 
  Paul C. Jeffries (@PaulJeffries) reported 31 minutes ago

  @petergyang I do that all the time. I switch models also. Switching models is harder because the context window size may differ and/or the tokenizer may have different resolution. But Anthropic has left us no choice because Fabel five is broken and often will not continue the conversation because it will not compact. So you have to switch to Opus 5 and get it to compact and then switch back. Sometimes you have to fork and do all sorts of pain in the *** things. But just switching whether thinking is on or off or the effort level, usually doesn’t affect anything because it’s an instant instantaneous runtime specification for the harness. There are cases where it could matter, especially as providers get mote fancy in what they’re doing hidden in the turn with multiagents and dialogues and such (you can surmise a lot of what anthropic is doing from bits of evidence of normal ops and leaks, which happen quite often — anyone else seeing the Opus 4.5 turn one that errors out and is the background process breaking out?). If you’re doing dependencies where what you process now and be the object of what you’ll process later, you may want to attach the model and effort data to the turn. Claude has an interior runtime report of what model it is, so you have set userPreferences to report it… but there has been a bug lately where the two different sources of such reports diverge, and it will sticky claim Fable 5 in the starting envelope even when you’ve switched to Opus 5 (which it will know about when it sees what it’s told about how to sign Github). As far as I know there isn’t an easy way to get it to self-report the effort actually executed (just what you request in the selector of course, but you have to hack that), but Claude Cowork does have a running tally of tokens consumed by processes it evokes (against at nominal budget of 15 million but it resets at certain ops boundaries), so I suspect that could be used. Of course, you could just use the wallclock, but that’s very rough — you’d want to track the intervals interior to the turn between the activity reporting lines. ChatGPT has its own versions of similar stuff but last time I checked was more opaque. Gemini I gave up on due to failures and an immoral privacy linkage to product affordances, so I don’t know. And Grok I’m not sure about either but it used to be unreliable on internal reporting. Do you keep in mind that any auditing or controls or reporting that you want to do about this sort of thing, for quality control or to make it more valuable to you later, you must do inside the turn because it is not available to the part of the system that talks with you after the fact. And things in the context window are reconstructed per turn in a way the systems don’t understand (so for example, a change in the envelope that occurs before the first prompt will be regarded by the system on turn 50 or whatever as having been there all along), so it can look like they are giving you authentic interior reporting and it’s just wrong even when it’s accurate in a sense.

• 
  Mark Kadirov (@KadirovMar13725) reported 33 minutes ago

  @josefchen @snowmaker @josefchen Hi Josef — Epicure MCP is still not working in ChatGPT. It returns 401 / authentication errors even though the docs say Auth: None. GitHub issue #9 is still open. Could you please take a look?

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  vechen (@miu21590) reported 33 minutes ago

  @CoderSafari by your logic, they could have been abusing it even without me, and just because the tool could theoretically be rewritten for abuse we could take down half of everything on GitHub my intention is to use the model quota I paid for in a way that's convenient for me, even with models that aren't available by default for coding (like Pro)

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  HOL (@HashgraphOnline) reported 36 minutes ago

  if you let AI agents run shell commands and touch your files, HOL Guard is the local policy layer that inspects every action before it executes and blocks the risky ones. open source, runs on your machine. 3.0 shipped this week, v3.0.0 through v3.0.12. the headline is managed controls: command catalogs for ***, AWS, gcloud, and Azure that know routine operations from destructive ones, so your agent stops asking permission for every *** status while the dangerous stuff still gets reviewed. the policy engine is Rust now, the single authority for pre-tool and post-tool checks, failing closed when a call can't be evaluated. you can enroll your own CLIs, npm scripts, and MCP servers as guarded extensions, and the dashboard detects locally installed AI apps, so unprotected claude code or codex installs show up instead of staying invisible. the rest was hardening. v3.0.8 closed parser bypasses: glob characters in diagnostic observers, decoy interpreter -c flags after a script path, GitHub mutations only skipped when &&/|| proves they cannot run. daemon recovery converges cleanly after tamper events, and AppImage launchers pin a durable CLI path. v3.0.9 put the macOS desktop engine on a stable, attested release channel. v3.0.10 makes auto/force hook review fail closed with no Python semantic fallback. v3.0.11 stops a transient sqlite error from wiping your policy history: quarantining the store now takes two consecutive fatal probes with the db, WAL, and SHM files provably unchanged, and legacy-home migration keeps your extension control settings. v3.0.12 accepts Linux desktop terminals for enrollment, bound to local session authority. uv tool install "hol-guard[cisco]==3.0.12"