I’m totally fascinated by AI coding stuff, but please don’t have an LLM write marketing copy and then shovel the first draft onto the internet. Particularly in a README which should be primarily technical.
The use of “Supercharge” and “Leverage”, the bulleted lists and the reams of non-information (glad to know this is good for “developers working on complex projects”) are all dead giveaways this is unedited LLM-generated content. More to the point, this writing style makes it difficult to tell which parts of the README have actually useful information and which parts of the README are just padding that’s there to waste my time.
As a result I’m gonna have to pass on this. Most LLM-generated READMEs I’ve seen have hallucinated installation guides and usage instructions, and I don’t have time to waste figuring out if that’s the case here. If you rewrite the README from scratch I’ll take another look.
The vision of unifying Copilot/Cursor/Roo/Cline/etc. under a common configuration and best-practice layer is compelling, and I like the direction toward reusable templates and memory.
That said, I think the project might be aiming a bit too directly at the highest level of complexity — the full integration of vibe-driven rules across assistants — without first grounding things in foundational concepts. Personally, I’d love to see a clearer breakdown of stages, such as:
1. Formal concepts of LLM-driven project management, akin to how we reason about conventional PM tools/processes.
2. Abstractions and interfaces to build structured rules/prompts (in the broad sense) that can be versioned, composed, and reasoned about.
3. Configuration management to deploy/adapt those rules across specific environments (LLMs, IDEs, agents).
Laying that groundwork could make the ambitious cross-assistant unification feel more achievable and less brittle.
Still, kudos — I think we need more of this kind of experimentation and discussion in the open.
I think this suggestion of polishing the basic layer first and then building the high level layer is a good one. Since the potential development directions are so broad (marketplace for rule sets, evaluation of rule sets, version control of rule sets, more useful tools, unit test & deployment & PM rules), I have never dared to over-design before users have clear feedback.
For project management, I have another exploratory project. This project is a set of rules that use Cursor/Cline/Windsurf as a project manager assistant.
repo is here: https://github.com/botingw/pm-workflow-copilot-ide
For your 2, I understand versioning with rules. Does compose mean assembling rules? What does reasoned about mean?
For your 3, what configuration management do you recommend adding?
> Supercharge Your
I’m totally fascinated by AI coding stuff, but please don’t have an LLM write marketing copy and then shovel the first draft onto the internet. Particularly in a README which should be primarily technical.
The use of “Supercharge” and “Leverage”, the bulleted lists and the reams of non-information (glad to know this is good for “developers working on complex projects”) are all dead giveaways this is unedited LLM-generated content. More to the point, this writing style makes it difficult to tell which parts of the README have actually useful information and which parts of the README are just padding that’s there to waste my time.
As a result I’m gonna have to pass on this. Most LLM-generated READMEs I’ve seen have hallucinated installation guides and usage instructions, and I don’t have time to waste figuring out if that’s the case here. If you rewrite the README from scratch I’ll take another look.
The vision of unifying Copilot/Cursor/Roo/Cline/etc. under a common configuration and best-practice layer is compelling, and I like the direction toward reusable templates and memory.
That said, I think the project might be aiming a bit too directly at the highest level of complexity — the full integration of vibe-driven rules across assistants — without first grounding things in foundational concepts. Personally, I’d love to see a clearer breakdown of stages, such as:
1. Formal concepts of LLM-driven project management, akin to how we reason about conventional PM tools/processes.
2. Abstractions and interfaces to build structured rules/prompts (in the broad sense) that can be versioned, composed, and reasoned about.
3. Configuration management to deploy/adapt those rules across specific environments (LLMs, IDEs, agents).
Laying that groundwork could make the ambitious cross-assistant unification feel more achievable and less brittle.
Still, kudos — I think we need more of this kind of experimentation and discussion in the open.
I think this suggestion of polishing the basic layer first and then building the high level layer is a good one. Since the potential development directions are so broad (marketplace for rule sets, evaluation of rule sets, version control of rule sets, more useful tools, unit test & deployment & PM rules), I have never dared to over-design before users have clear feedback.
For project management, I have another exploratory project. This project is a set of rules that use Cursor/Cline/Windsurf as a project manager assistant. repo is here: https://github.com/botingw/pm-workflow-copilot-ide
For your 2, I understand versioning with rules. Does compose mean assembling rules? What does reasoned about mean?
For your 3, what configuration management do you recommend adding?
Yes, I agree. This feels very complex for something that is supposed to support vibe coding.
This readme is so hard to... read.