superpowers VS cli

It's crazy to me that some GitHub repos, that were just created in the last year, have more stars then some of the most popular programming frameworks out there. At the time of writing, Superpowers, is around 226,000, ahead of the Vue repo and way ahead of Next.js. A separate repo based on Andrej Karpathy's coding advice has 174,000. And they aren't even code. They're folders of markdown files that tell your AI coding agent how to write software better.

Meanwhile, the ecosystem materialized. obra/superpowers shipped a complete software development methodology built on composable skills — 1,276+ stars and growing. The cobusgreyling/loop-engineering repo cataloged patterns from Osmani and Cherny into a practical reference.

Projects like Superpowers proved that agents can follow structured methodologies — brainstorm before coding, write tests before implementation, review against specs before declaring success. The skills are mandatory workflows, not suggestions. The agent checks for relevant skills before any task.

If you're looking for complementary skills and plugins then have a look at Addy Osmani's Agent Skills or Superpowers, both provide essential coding assistant skills like Test-Driven Development (TDD). OpenSpec provides consistency, and your workflow can evolve around it.

Before any implementation, I plan. I use the brainstorming skill from Superpowers to think through the approach, then Grill Me - a separate skill that probes for contradictions, gaps, and missing assumptions, question by question. Once I'm satisfied, I save the result as a PRD and move to writing-plans (also from Superpowers), which produces a detailed implementation plan: class names, properties, architecture, tests.

These don't replace the spec; they govern how the agent acts on it. Superpowers uses guided Q&A to clarify intent, then runs sub-agents behind a verification-before-completion gate. GSD manages context in waves for solo developers. HVE Core runs an RPI loop: Research, Plan, Implement, Review.

> It would be extremely cool to be able to write one or two lines of prompt in my harness, and have a light model iterate with me a few times writing/proposing requirements, guidelines and explanations, refining the prompt until it's ready to be sent to the actual LLM.

I feel like the vast majority of AI-using coders already do this via skills suites like Superpowers (see /superpowers:brainstorming), no? https://github.com/obra/superpowers

I joined Entire because our convictions aligned: we need to fix the structural breakdown in open source. Right now, we have built a CLI that provides a system of record that captures the context behind agent-assisted code changes. The record gets stored as a This serves as the baseline for a new era of developer tooling that can help our industry move towards:

Your coding agent sessions belong in your codebase. Before I joined Entire, the company building the infrastructure to bring your agent sessions into your code, I was already exploring this exact idea on my own.

Looks super interesting - this tool (open source) captures your agent AI session alongside your code commits. Works with multiple coding agents. - link [tool] - ( Added: 2026-05-06 16:45:22 )

just curious since it reminds me a bit. Have you / someone tried https://entire.io/ (I'm not affiliated at all, so it is not a plug).

Check out Entire at entire.io

Git tells you what changed. Entire tells you why, and who. Or what.

Let me rewind for a second and introduce you to Entire. Entire is the company I work for. We're building the next developer platform for the AI-native software development lifecycle. The team recognized that agents have changed our workflows, so the infrastructure we use should change too.

TL;DR Install Entire right now.

This is what the Github CEO recently announced as a product/company:

https://entire.io/

Original blogpost goes over motivations + workflow:

https://entire.io/blog/hello-entire-world/