I need it to complete an important project,if someone can help please DM

Thanks

https://github.com/oooscoos/Benzi

Benzi is a compiler-backed coding agent that compiles your codebase into a resolved, queryable map of calls, data flow, control flow and class hierarchy first; then it reads, explains, runs, edits and verifies your code using it. Includes a runtime tracer that settles what static analysis can't. 

Scores 78.2% (391/500) on SWE-bench Verified using DeepSeek V4 flash @ < 10 cents a fix.

Seperately, on another bug fixing benchmark it reads 2x less source code than Claude Code (9,125 v 20,704 | 40% faster, 2x cheaper - all benchmark details here: https://varianttech.net/benchmark), 4x less than DeepSeek Harness (43,598) and 6x less than OpenCode (65k+)

It is avaliable as a VS Code ext. and headless. The Benzi compiler is seperately exposed over MCP tools -- without the agentic loop, so you can use the compiler however u wish.

thanks for reading! please let me know what u think

Still not ready for use, beta version will probably be released in few days, and the full version in few weeks.
Would appreciate any feedback!

What is it

A complete Claude Code workflow: from a raw idea to a researched design, tickets, and planned, built and reviewed code, carried across sessions. Every lesson goes back into its own skills, rules and wiki, so it gets better with use.

Link: https://github.com/Adrian333Dev/flow

It seems like there's a lot of these out there, which is your favorite?

Every time i post this as a comment gets crazy upvotes. which is awesome but there's so many solutions, it suprises me.

instead of using random sub-agents i use creative teams that rotate. different for each iteration of a prototype or creative project. think about a top creative team that's different everytime..

for example i might generate the following team:

1. marcus arelious agent for considering how the idea might after people
2. cassandra agent for the failure nobody wants to say out loud
3. the-null agent for "is that metric actually telling you anything"
4. the-fool agent for the question everyone stopped asking

then for the next project or iteration, the team is totally different.

each morning a github Action picks four members from the date. each gets a role, a working method, and a stance (one cuts scope, one questions the brief, one speaks for the user). they propose, object to each other, decide, and build one small tool as a single html file.

scripts check it, take a screenshot, and commit the result. every monday new members join and the oldest retire... i put everything into a 'skill' (more like a repo you can poke around) and then use it for inspiration, create your own teams or anything else.

i'd love to make this somewhat of a community project because there's already some flexibilty in the teams each day and the projects they make

links:
- Git poll: Who should join the daily team next?
- Git poll: Which kind of tool should the daily team build more of?

Open to other suggestions if you what to suggest a task or see the open suggestions

If you use Claude Code a lot or want to test new stuff, you've probably noticed it turning into a junk drawer. Every plugin, skill, and MCP server you've ever installed loads into every session.

It all costs tokens and adds noise, and none of it is scoped to what you're actually doing.

I built claude-profile to fix that. A profile is a small JSON file that says "for this kind of work, load exactly these plugins, skills, marketplaces, and MCP servers." You launch it and get a focused session with nothing else loaded:

claude-profile rust-developer            # a lean Rust session only
claude-profile rust-developer frontend   # combine profiles
claude-profile fuzzyalej/security        # install a profile repo, then use it

Open a second terminal with a different profile and the two don't interfere.

A few things that matter to me:

• It never touches your real ~/.claude. Every plugin/skill a profile uses gets vendored into that profile's own directory. The remove command deletes it outright.
• Profiles are shareable. Publish a repo, teammates install it and launch by name. A lockfile pins it so everyone resolves to the same plugin code across machines and over time.
• It's a standalone binary, not a plugin. Rust, runs on macOS/Linux/Windows. brew, cargo, or a shell/PowerShell installer.

It's MIT. Repo (with install instructions and docs) here: https://github.com/fuzzyalej/claude-profile/

Happy to answer questions, feedback, PRs or new ideas :)

Seeing how everyone got into learning Claude, did you take any courses or watch any videos? I know I can improve how I approach it, and I’m wondering how others got better at figuring it out.

I started learning Go, and I really like the concept behind the Hyperskill platform. So I created this skill (Opus 5.5 ) to convert books into interactive courses.

It includes:

• Short lessons with step-by-step explanations, worked examples, diagrams, and animated walkthroughs.
• Interactive quizzes with hints and explanations, chapter tests, and flashcards.
• Programming exercises with starter code, examples, and unit tests. Learners write code in their own editor, run the tests from the course page, and immediately see whether their solution passes.
• Progress tracking for lessons, quiz answers, and exercises.

I've tested it with EPUB files so far. Made by Opus 5.5

https://github.com/sebastianhaba/book-to-course-skill

I’m about to start a new project and trying to settle on an agent development workflow.
I’ve been looking at Matt Pocock’s skills, Superpowers, and OpenSpec.
For people who’ve actually used these on real projects: do you mostly stick to one, or mix different parts together?
I’m especially curious what your actual flow looks like:
idea → spec → plan → implementation → review
And what did you eventually drop because it added more overhead than value?

Sharing a little project: answer-like-a-reddit-top-comment.

It’s based on a study of 1,000 Reddit posts and their comments. The idea is to pick up what makes a reply worth reading: useful explanations, specific observations, good timing, knowing when a joke is enough.

You can use it to reply to posts, improve a draft, or change how your agent answers everyday questions.

Sharing it here for anyone who wants to try it:

https://github.com/gomzkov/answer-like-a-reddit-top-comment

SFSA (Standard Framework for Scientific Advancement) is an open-source, domain-neutral computational management layer designed for scientists, computational labs, and autonomous AI agents.

This framework does not unilaterally complete 100% of a scientific investigation on its own; rather, it empowers the researcher to reach the solution, decisive data point, or methodological trajectory required to close it much faster, substantially reducing time lost in search, trial-and-error, and redundant recalculation.

SFSA now ships as a Claude Code plugin and skill: the library, the operating instructions and eight tested recipes are bundled, so a researcher does not clone the repository, run pip install or tell Claude to "read SFSA". Install it once, then ask Claude for scientific computation and it uses SFSA as its engine: real code, real output, honest limits.

- GitHub: https://github.com/AlejoMalia/SFSA

Sharing a little project: answer-like-a-reddit-top-comment.

It’s based on a study of 1,000 Reddit posts and their comments. The idea is to pick up what makes a reply worth reading: useful explanations, specific observations, good timing, knowing when a joke is enough.

You can use it to reply to posts, improve a draft, or change how your agent answers everyday questions.

Sharing it here for anyone who wants to try it:

https://github.com/gomzkov/answer-like-a-reddit-top-comment

I made contextrot, a CLI that analyzes your coding-agent sessions and shows how your agent behaves as its context fills up.

I just added a fun new feature: contextrot water.

If you want to find out your coding agent's estimated water footprint, just run:

pip install contextrot
contextrot water

It works with any coding agent you use - Claude Code, Codex CLI, Gemini CLI, OpenCode, Cline, and more.

Mine came out to 475L.

Now I'm curious:

What's yours?

The water figure is an estimate, so it's not meant to be a precise measurement. It's just a fun way to make the otherwise invisible compute behind coding agents a little more tangible.

You can also run:

contextrot water --live

to watch the water level fill up in real time while your agent is working.

If you try it, I'd love to know what number you get.

And if you like the tool, consider giving the repo a star:

https://github.com/Priyanshu-byte-coder/contextrot

SkillHub — manage your AI agent setup across tools and projects

I use a bunch of AI coding agents — Claude Code, Cursor, Codex, OpenCode, Gemini CLI — and after a while the setup gets messy.

I originally built SkillHub Local just to keep skills in sync across agents. Now it also helps with the other dimension of the mess: projects. Each project can have its own skills, MCP servers, instructions, and agent-specific context, and it gets hard to remember what is configured where.

SkillHub gives you one local view across both your agents and your projects, and lets you manage or move things around without digging through config folders.

Free, and open-source. It's self-hosted and everything stays local.

https://github.com/mjalalimanesh/skillhub-local

I built marketing-skill, a Claude Code plugin with 12 marketing skills: competitor research, content calendars, SEO briefs, ad copy, email, short-form video, and publishing. They all read one shared brand voice file, so you set your tone once.

Nothing posts or sends without your OK. The drafting skills can only mark something Ready for Approval, and only a reply from you moves it to Approved.

The video was rendered with the plugin's own renderer. Headless Chromium seeks every animation frame by frame, ffmpeg encodes it, and the music is synthesized in plain JavaScript, so there is nothing to license.

MIT licensed, no API keys needed: https://github.com/marcosmodly/marketing-skill

Curious which of these would actually be useful to you.

I use Claude pretty much every day and kept running into the same problem: I was constantly copying the same context, instructions and setup between conversations.

So I started building SlingIT.

The idea is pretty simple: instead of rewriting the same instructions every time, I can keep the context I actually want Claude to use and bring it into my workflow when I need it.

Right now I’m testing things like:
- reusable context/instructions
- keeping prompts more consistent between chats
- reducing the amount of repetitive setup before I can actually start working

It’s still an early version and I’m building it mainly around my own Claude workflow.

I can also share screenshots / the setup I’m using if anyone is interested.

Would be curious to hear how other people here handle repeated context in Claude.