superpowers
chardet
| superpowers | chardet | |
|---|---|---|
| 71 | 32 | |
| 223,236 | 2,635 | |
| 22.7% | 1.1% | |
| 9.7 | 9.8 | |
| 3 days ago | about 1 month ago | |
| Shell | Python | |
| MIT License | BSD Zero Clause 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
chardet
- Grit: Rewriting Git in Rust with Agents
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The Claude Code Source Leak: fake tools, frustration regexes, undercover mode
It seems like it's an active area of legal thought (IANAL though).
Recent relevant discussion about this in the chardet repo between the chardet maintainer who relicensed the code and Richard Fontana, a well regarded lawyer US IP lawyer who's worked for Red Hat (not IBM) for decades:
https://github.com/chardet/chardet/issues/334#issuecomment-4...
My take away from the conversation there is that being in an edit loop, where the files are AI generated through your control rather than directly editing the files yourself, means the files are then "AI authored" for copyright protection purposes rather than yourself.
But I double stress, I'm not a lawyer so may have misunderstood things radically.
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Source code is now a common good, and SaaS is mostly dead
Around the same time, someone attempted exactly this with the chardet Python library—using Claude to rewrite it from LGPL to MIT. The open source community was furious.
- Malus – Clean Room as a Service
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Debian decides not to decide on AI-generated contributions
You can "relicense" it as you see fit, but anyone can just copy it and ignore your license and its terms entirely, it's not your property to put a license on.
See also Red Hat IP lawyer's opinion on trying to license the chardet "rewrite": https://github.com/chardet/chardet/issues/334#issuecomment-4...
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Is legal the same as legitimate: AI reimplementation and the erosion of copyleft
> The dispute drew responses from two prominent figures in the open source world.
Sure, but neither of those is an IP Lawyer.
The actual IP Lawyer that showed up and tried to engage had his issue closed:
https://github.com/chardet/chardet/issues/334
- Chardet v7.0.0 presents unacceptable legal risk to users
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AI and the Ship of Theseus
> Right now I would argue that unless some evidence of the contrary could be provided, this can be seen as a new implementation from ground up.
Not ship of Theseus, but a "new implementation from ground up.
Evidently, the author prefers MIT (https://github.com/chardet/chardet/issues/327#issuecomment-4...), and seems OK with slop-coding.
- Coding agent rewrites (and improves) LGPL library and releases under MIT license
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No right to relicense this project
> You have to prove [..] that the defendant made an unauthorized derivative work
You only need to prove that they made a derivative work; the derivative work itself is authorized as long as the license is obeyed. And it's very easy to prove they did: there is a linear progression from the original LGPL-licensed code to the current codebase, in the form of a Git history: https://github.com/chardet/chardet/compare/6.0.0.post1...7.0...
Every single commit there is a derivative work of the work before. No attempt was made to do a piece-wise replacement of features by isolating each feature (either via API or test behaviour), abstracting its behaviour and then reimplementing it. So this is not even a Ship of Theseus question: if every single part of the ship was replaced but the shape is the same, is the current ship a derivative of the original?
What are some alternatives?
BMAD-METHOD - Breakthrough Method for Agile Ai Driven Development
Charset Normalizer - Truly universal encoding detector in pure Python.
spec-kit - 💫 Toolkit to help you get started with Spec-Driven Development
ftfy - Fixes mojibake and other glitches in Unicode text, after the fact.
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.
shortuuid - A generator library for concise, unambiguous and URL-safe UUIDs.