Entries matching “github”

GitHub

@github

GitHub 🤝 @Muse A new way to connect your GitHub account to review PRs, catch up on issues and notifications, and leave comments without switching tabs.

@QuJindai

@QuJindai

A Muse skill and thin gh-style CLI for the GitHub REST API that authenticates through a stored custom.github connector, so the skill never handles the raw token.

Browserbase

@browserbase

Browserbase is now available as a plugin in Muse Code. Get started with two commands: > muse plugins marketplace add browserbase github.com/browserbase/br… > muse plugins install browse@browserbase

@fengyiqicoder

@fengyiqicoder

A serverless, read-only Muse connector hosted on GitHub Pages: an OpenAPI document plus JSON conversation playbooks for declining, apologising, negotiating, following up and other hard messages.

A Muse agent receives a one-time secret two ways: the hard way (email link, redacted URL, dropped decryption key — 45 min) and the agent-native way (a Claude agent creates the request with one Qatom call + ~$0.10, the Muse agent retrieves with one free call — 2 seconds, secret delivered once then deleted). Secure Secrets Exchange on Qatom. Tool: https://github.com/StarwaterHeaven/secure-secrets-exchange — full story: https://github.com/StarwaterHeaven/qatom-use-cases/blob/main/stories/sse-credential-handoff-torque.pdf

Moss AI Studio 🌱

@MossAIStudio

Loving it! I did a 2026 remake of my Spooky Clicker the other day and the total was $0.63. Lots built too! Changelog for everything is here: github.com/DevTarlow/spoo…

rohanadwankar.github.io

rohanadwankar.github.io

Rohan Adwankar found Muse runs on Cloud Hypervisor microVMs with a 327 MB Rust harness that boots in ~40 s, an on-VM Postgres with 194 tables and 60+ privsep tool workers.

@gosukiwi

@gosukiwi

Federico Ramirez uses Muse Code and Spark 1.3 for GitHub issue-to-PR workflows. He finds output readable and $15/month good for 2-4 hours of continuous coding, but skill execution inconsistent and the sandbox too restrictive.

taylorarndt.substack.com

taylorarndt.substack.com

Taylor Arndt retried Muse after Meta Connect with Gmail, Google Calendar, GitHub and her own product-management tool connected, and found it inferred her COO role from calendar data and became useful for ongoing task management.

Dmitry Korzhov

@korzhov_dm

holy shit, @Muse just caught $1,742 a week leaking out of my ad account I asked one question about my ad spend. It did everything else by itself: > Pulled Meta, my pixel and GA4 and noticed the numbers didn't match > Split it by age, device and creative, found 4 dead ads eating

meta.com

meta.com

Meta's Connect 2026 roundup: Muse voice mode, the Muse Realtime Avatar, Muse on AI glasses, an agent email address, Mac computer use, and connectors from Walmart, Best Buy, Expedia, Instacart, Notion, GitHub, Box and more.

My fun weekend project was to try to make the new Muse Glimmer 30B work with a longer context, deciding to go for 512k first. I had expected the usual YaRN shenanigans and maybe a LoRA. I couldn't have been wrong more. Upon closer look, Glimmer turned out to be rather unusual architecturally. The thing that make long-context adaptations painful in other models, full attention layers with token position encoding, it simply not there. Instead, only 2048 tokens-wide SWA layers have RoPE, and full GQA attention layers have no position encoding at all. It appears the model is trained to work with long-distance token relationships inferred from the context and SWA layers. It's a rather bold architecture bet, but it seems Meta managed to pull it off. As a result, the model architecture appears to be uniquely suited for context extension by simple mechanical means. To change model context length from stock 128k to, say, 512k, you need only to change “max_position_embeddings” config setting from 131072 to 524288. What confuses other models, like Qwen3.5 family, Glimmer just takes into its stride. I spent close to 70h of compute on DGX Spark to test stock model with extended context on a

@sureshsankaran

@sureshsankaran

A Muse workspace skill for managing GitHub repos through the REST API, including pushing directories via the Git Data API, with the token kept in the Muse vault.

Jacob Mitchell • FermentIQ

@jacobdmitch

Yes! I’ve already connected mine to @getFermentIQ @render @ElevenLabs @TransistorFM @github and more!

@Rutvik1337

@Rutvik1337

A gallery of 100 single-file HTML pages one-shotted with Muse Spark 1.3 Contributor, with a searchable catalog page and inline previews on GitHub Pages.

Anonymous

github.com

A working mobile-friendly web app built by the Meta Muse personal agent from a real courier's detailed requirements. It compares DoorDash/Uber Eats delivery offers after total miles (including empty return), waiting time, all-in vehicle costs and tolls. The surprising demo: a $9 offer can yield $19.08 net per hour while a $20 offer only yields $16.09 under stated assumptions. Muse created the standalone offline HTML and logic tests (49/49 self-reported); I downloaded it, independently verified actual browser inputs/outputs, published the source and proof screenshot to GitHub, and deployed a no-signup live demo. Live app: https://boyhoangxattpt2-blip.github.io/gig-driver-profit-checker/ . GitHub README includes exact math, source code, build story, and reproducible prompt.

@axlecoffee

@axlecoffee

A BYOK VS Code extension that registers the InferHub catalog, including Muse Spark with its 1,048,576-token context window, as a model provider in the Copilot Chat picker without Copilot Pro.

techcrunch.com

techcrunch.com

TechCrunch's Connect roundup: retail connectors (Walmart, Best Buy, Gap, Sephora, Wayfair), Shop Pay and PayPal checkout, GitHub/Granola/Notion connectors, 1,500+ developer applications in a week, and Zuckerberg's plan to profit from a small fee on transactions.

LLMs have become extremely good at coding, maths etc, but how well do they do at playing a simple dungeon/maze game that even a child can solve easily? The LLM has to navigate a 10x10 grid map, completing objectives in the right order (collect weapon > kill monster > head to exit) while navigating the dungeon and avoiding walls. Three illegal moves fail the run. All models are tested with reasoning enabled. The code and more info on my GitHub if you want try it yourself: https://github.com/shinomakoi/dungeon-bench Model leaderboard: Model Score DeepSeek-V4-Pro (high) 🥇12/12 Gemma-4-31B-it 🥈11/12 Qwen-3.8-27B (medium) 🥈11/12 GLM-5.3-Flash (high) 🥈11/12 Muse-Glimmer-30B (medium) 🥉10/12 DeepSeek-V4-Flash (high) 🥉10/12 Granite 4.2 (full) 8/12 KAT-Coder-V2.5-Dev 8/12 Nemotron-3.5-Lightning-30B-A3B 5/12 Model Illegal moves DeepSeek-V4-Pro (high) 🥇0 Gemma-4-31B-it 🥈1 Qwen-3.8-27B (medium) 🥈1 Muse-Glimmer-30B (medium) 🥉2 Granite 4.2 (full) 🥉2 Nemotron-3.5-Lightning-30B-A3B 7 GLM-5.3-Flash (high) 8 KAT-Coder-V2.5-Dev 10 DeepSeek-V4-Flash (high) 12 DeepSeek-V4-Pro: By far the best result. Basically perfect performance in all maps.

This is a small HTTP API you run on a machine you control. Muse SSHes in and calls http://127.0.0.1:8792. It can search Amazon and add to a personal cart or a Prime Business cart. It does not check out or pay. https://github.com/aasper03/muse-amazon-bypass You need Python 3.11 and curl. Sign in to Amazon in a normal browser and export cookies for each account. Amazon blocks automated login windows. The README covers Muse-over-SSH setup, and a later section shows how to call the same API yourself.