superpowers
gsd-2
| superpowers | gsd-2 | |
|---|---|---|
| 71 | 5 | |
| 223,236 | 7,738 | |
| 22.7% | 10.6% | |
| 9.7 | 9.9 | |
| 3 days ago | 22 days ago | |
| Shell | TypeScript | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
superpowers
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Loopcraft: Stop Prompting, Start Designing Loops
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.
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From Fallacies to Superpowers: Eight Agent Skills That Make AI-Assisted Development Work
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.
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Spec-Driven Development with OpenSpec
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.
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What I Got Wrong About Claude Code (And How I Fixed 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.
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Spec-Driven Development: When Structure Helps and When It Becomes Tax
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.
- Codex app plugin integration can be better?
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Show HN: Promptloop – create, run, and improve prompt evals from the terminal
> 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
- Superpowers: An Agentic Skills Framework for AI Coding Workflows
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How I Make Claude Code's 5-Hour Usage Window Last Longer on Claude Pro
I sometimes use Superpowers skills such as writing-plan and writing-spec. The Superpowers brainstorming skill stores design specs under docs/superpowers/specs/YYYY-MM-DD--design.md, and the writing-plans skill stores implementation plans under docs/superpowers/plans/YYYY-MM-DD-.md. (GitHub, GitHub)
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How Superpowers Forces Skill Execution
obra/superpowers – GitHub
gsd-2
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Lessons for Agentic Coding: What should we do when code is cheap?
It seems there is a new version [1] - I'll try it out and see if it is better.
[1] https://github.com/gsd-build/gsd-2
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Your AI is confident. Your AI is wrong. You shipped it anyway.
GSD has beautiful structure. Milestones, slices, tasks. Discipline is the user's job. The framework doesn't enforce it at the worker level.
- A Rave Review of Superpowers (For Claude Code)
- GSD 2
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Get Shit Done: A Meta-Prompting, Context Engineering and Spec-Driven Dev System
I have been using this a lot lately and ... it's good.
Sometimes annoying - you can't really fire and forget (I tend to regret skipping discussion on any complex tasks). It asks a lot of questions. But I think that's partly why the results are pretty good.
The new /gsd:list-phase-assumptions command added recently has been a big help there to avoid needing a Q&A discussion on every phase - you can review and clear up any misapprehensions in one go and then tell it to plan -> execute without intervention.
It burns quite a lot of tokens reading and re-reading its own planning files at various times, but it manages context effectively.
Been using the Claude version mostly. Tried it in OpenCode too but is a bit buggy.
They are working on a standalone version built on pi.dev https://github.com/gsd-build/gsd-2 ...the rationale is good I guess, but it's unfortunate that you can't then use your Claude Max credits with it as has to use API.
What are some alternatives?
BMAD-METHOD - Breakthrough Method for Agile Ai Driven Development
probe - AI-friendly semantic code search engine for large codebases. Combines ripgrep speed with tree-sitter AST parsing. Powers AI coding assistants with precise, context-aware code understanding.
spec-kit - 💫 Toolkit to help you get started with Spec-Driven Development
open-artisan - OpenCode plugin for structured AI workflow orchestration
claude-code - Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands.
claude-forge