superpowers VS plannotator

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 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)

obra/superpowers – GitHub

I do think this style of working is where software engineering work is heading. This style is essentially exactly what my workflow is today using _insert agent harness here_ + plannotator[0]. Linear also recently rolled out something very similar for reviews[1]. The working style of spec driven dev, following by fast code reviews using tools like plannotator/linear/command center seems to be where we are headed, and more more tools like it are popping up nowadays.

0: https://plannotator.ai/

I use Claude Code, Codex, Pi all for varying levels of work.

I like reviewing agent messages, some specs/plans, and then conducting local code reviews with Plannotator [1].

For skills, i really only like using the interrogate skill from cursor's lauren [2]. I use with claude and codex models.

[1] https://plannotator.ai

[2] https://github.com/cursor/plugins/blob/main/pstack/skills/in...

I do think Cloudflare probably institutes a similar manual review process as well. I have a handful of fairly vocal and supportive engineers I stay in contact with around https://plannotator.ai (there is an integrated code review surface that creates a feedback loop with your local agent).

> agents do a good job of looping over PR comments

This is the easy part. Most harnesses enable some sort of integration now, so you can actually create a smooth local experience around this as well - better code before it ships to more costly review or bloats PR threads.

> guided, educational code review tool

This is a bit tougher, and I find the main harness chat tends to work best. I learn better when I'm more engaged and aware of what I'm asking. It's easy to stick a code tour type of thing on a screen. It's hard to really nail the right attention and learning mechanism around it.

It never worked well for me. The only thing I really needed outside of the harnesses was a better plan review surface. https://github.com/backnotprop/plannotator

Plannotator, open source runs locally, has code review: https://github.com/backnotprop/plannotator

and a code tour feature about to ship: https://x.com/backnotprop/status/2043759492744270027/video/1

- integrated comment feedback for agents