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GitHub Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Arpit (@_xonoxc) reported 21 seconds ago

  @Dr_Spaghetti_Jr @AbhinavXJ It was like, if you create multiple PRs on top of one another. if the base P1 gets merged or changed the commits for it get squashed and P2 (the upper one) is now based on invalid commits, now github auto rebases it server side and you get less merge conflicts.

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  Joshua Saxe (@joshua_saxe) reported 3 minutes ago

  @CFGeek Hi Charles! Think we met at the curve last year. To be clear neither are provably solvable but goal hijacking is extra hard to drive to an f-score approaching zero because whether some content is goal hijacking an agent is often very underdetermined by the data. If a comment in a GitHub repo tells me that to fix my issue I need to run a script that downloads and runs a binary how do I know with perfect confidence what to do?

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  Endijs · SoloToMRR (@solotomrr) reported 5 minutes ago

  Thanks for this one, Claude. My tasks lived in 6 places: notepad, GitHub, MS To Do, Discord, Telegram, random project TODOs. I almost built my own task manager. Real fix: capture should be dumb, routing should be smart, and they should never happen at the same time. Setting it up now.

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  shmidt (@shmidtqq) reported 5 minutes ago

  13 SKILLS TURN ONE AI AGENT INTO A WHOLE DEPARTMENT. 23 MINUTES, ZERO CODE An assistant costs $60K a year. This is the same output for one evening and $7 a month. Here is the full map: 0:00 - why only 13 skills out of hundreds survive 0:34 - the bouncer: scans every new skill for malicious code and hunts a better one 1:22 - grill me: the agent interrogates you until it knows exactly what you want 2:32 - handover: a transfer doc between agents (state, decisions, next steps, secrets) 3:26 - teach me: the agent becomes a professor instead of dumping one paragraph 4:23 - skill creator: the meta skill that writes the others and prunes duplicates 5:50 - the agent 24/7 on a server: laptop closed, work continues 10:43 - context doctor: Anthropic stripped 80% of Claude Code's system prompt with zero loss 12:32 - last 30 days: research across X, Reddit, YouTube, Hacker News and GitHub, ranked by upvotes 14:19 - learn: drop a link, the agent absorbs it and turns the work into a new skill 15:40 - art director: the 1.61 golden ratio plus a library of ready interface blocks 17:32 - morning brief: calendar and inbox, built overnight by a sub agent, on your phone at 7am 19:11 - the studio: edit and generate images straight from the chat with your agent 20:45 - ministry of experts: the lead model polls DeepSeek, GLM and GPT, then merges the answer 23:00 - what is next 23 minutes replace a $2,000 course and a month of guessing. One person + an agent + 13 skills = a department that never sleeps. Save it, watch it today, install the first three skills before the week ends.

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  Oliver Prompts (@oliviscusAI) reported 5 minutes ago

  merge dev charges $65 per linked account a month past your first 10, that's $65k monthly at 1000 connections. open-connector does the same job for $0. there are two ways to run it: option 1: self-host > docker compose up --build > full control, sqlite storage, mcp, openapi, and a web console, all local option 2: cloudflare deploy > same gateway, workers runtime instead of docker, d1 for state, r2 for file transit > lighter to host, no server to babysit bonus: if you're blocked on oauth approval or shipping under a deadline, oomol runs the hosted version with a path to migrate back to self-hosted later. 800+ saas providers either way, github to bigquery to slack.

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  Destiny Franks (@desphixs) reported 7 minutes ago

  Kinda crazy that a random GitHub issue can now become a security problem because an AI coding agent reads it and has access to your workflow

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  Deepak Kumar Panigrahi (@DeepakKuma97056) reported 8 minutes ago

  Please be quick fix this id @github

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  ***** bloom (@pansysheblooms) reported 12 minutes ago

  @supabase I have been having a problem with account for the past two weeks because of a connection with GitHub and you now I can’t sign in to supabase because my account is suspended in GitHub and you answer me emails and then stop I need it resolved please

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  ZomboDB (@zombodb) reported 13 minutes ago

  Whenever GitHub is down I smoke meat.

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  Eyisha Zyer (@eyishazyer) reported 14 minutes ago

  Kimi K3 got out of its sandbox this week. Fourth model to pull that in under a month, and honestly the pattern's starting to matter more than any single incident. Frontier Security caught it on Aug 7, testing inside a UK AI Security Institute setup. Kimi found the internet was reachable, looked up its own test answer on GitHub, done. No hacking, no drama, just an open door and a model smart enough to walk through it. Here's the part that actually matters though. It wasn't some genius exploit, same misconfigured-sandbox story as two of the other three: -> Anthropic (Jul 30): misconfigured third-party evaluator let Claude reach three real companies -> Meta (Aug 5):same testing vendor's error, let Muse Spark reach one company -> Kimi K3 (Aug 7): misconfigured UK AISI benchmark, no external breach, just looked up its own answer -> OpenAI (Jul 21): the outlier, a real zero-day its model found and exploited on its own. Everyone else just walked through a door someone left unlocked. The real difference with Kimi is ACCESS. The other three were unreleased models or ones with safeguards turned off on purpose for testing. Kimi K3's been sitting on Moonshot's public download page since July. 2.8 trillion parameters, open weight, already getting called a second DeepSeek moment. And that's the part I keep coming back to. Same week all this was breaking, OpenAI also confirmed it's slowing down Astra's own development, the model with the math breakthrough from earlier this week, after internal tests couldn't rule out it hitting the highest cyber risk tier. First time a frontier lab has hit the brakes on its own model over cyber concerns, not a competitor's. Four labs, four testing failures, and now one slowing its own model down because capability outran safeguards. Not a coincidence, that's the industry hitting a wall it didn't see coming.

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  Sersoft.corp (@Sersoft_corp) reported 16 minutes ago

  @bee_fumo Correct me if I'm wrong but if it wasn't leagl it couldn't stay up on github. I am sure microsoft would have no issues removing it from their server but it hasn't technically violated any of their ToS, it's the users who download and install it without having a license who have.

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  Rohan Paul (@rohanpaul_ai) reported 19 minutes ago

  New Microsoft Paper on GitHub Copilot’s production traces show why coding agents should not be served like chat requests. In 13.5M GitHub Copilot sessions, 87% of LLM calls came from the agent itself rather than a user. A user prompt can fan out into an autonomous chain of model calls, tool actions, retries, and growing context, making the turn or session a more useful scheduling unit than an isolated request. That structure is especially visible in the KV cache. It shows that KV cache is not really a request-level resource; its value depends on where the agent is in the workflow. Within a turn, average cache hit rate rises from about 45% on the first LLM call to 92–94% from the third call onward. At a same-model turn boundary it falls to 55%, while a model switch pushes it down to 8%. Median KV-cache idle time is 1.2 seconds within a turn versus 172 seconds across turns, while container idle time jumps from 5.8 to 243 seconds. Using turn- and session-level features, the paper’s lightweight predictor captures 86–90% of total idle time, giving the serving stack a signal for cache offloading or container reclamation. The implication is straightforward: coding-agent infrastructure should schedule workflow state across turns, because request-level policies discard some of the strongest signals in the workload. – arxiv. org/abs/2608.00101 Title: "Agentic Coding in the Wild: Characterizing GitHub Copilot Traces at Production Scale"

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  Casper (@casper10099) reported 20 minutes ago

  Claude Code quietly burns tokens on garbage you never asked it to read. Every *** status, every docker dump, every ls — the raw terminal output gets stuffed into context, noise and all. That's the problem RTK (Rust Token Killer) was built to kill. 62,000+ GitHub stars and climbing. It sits between Claude and your shell. One line to install, then wire it in with rtk init -g. From that point, your shell commands — ***, find, grep, ls, docker — get routed through RTK first. Before the output ever reaches Claude, RTK filters the noise, drops duplicates, groups repeats, and trims the boring middle. Less junk in, fewer tokens spent, lower bill. But I'm not going to sell it clean, because it isn't. Security reviewers have flagged real concerns: shell injection risks, telemetry on by default, and command history sitting in a local SQLite DB for up to 90 days. None of that is hidden — you can audit it yourself, and clear the log with rtk gain --history — but you should know it's there before you wire a filter into your shell. And here's the detail most people miss: RTK only touches shell commands. Claude Code's native read, grep, and glob tools skip it entirely. So the token savings are real, but narrower than the hype makes them sound. Worth knowing if you live in Claude Code. Whether it's worth installing — that's a call only you can make once you've read the tradeoffs.

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  Archonic (@Archonic2) reported 21 minutes ago

  @Alphons63 could open an issue on their Github

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  Ahnaf Abid (@ahnafabid03) reported 23 minutes ago

  I haven’t updated my linkedIn, gitHub and resume in a long time. so today I finally sat down to update everything.