muster / rules
Cursor rule40 starsChanged 10 months agoApache-2.0View on GitHub
Instructions for AI/LLM assistants
2 other projects use a version of this.
Adopted by
Most recently taken up by
- giantswarm/mcp-kubernetesword for word, first seen Nov 6, 2026
- giantswarm/agent-managerword for word, first seen Oct 9, 2026
Other versions2 projects use a version of this.
Word for word · 2
- giantswarm/mcp-kubernetes★ 2100% same
- giantswarm/agent-manager★ 0100% same
Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
Where files are headingNew Cursor rule files have more rules about planning and tracking tasks, and fewer about code style.
Of the Cursor rule files we read, the 4,157 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repository5 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .cursor/rules/architecture.mdcCursor rule
- .cursor/rules/github-workflow.mdcCursor rule
- .cursor/rules/mcp-debugging.mdcCursor rule
- .cursor/rules/zz_generated.go-llm-rules.mdcCursor rule
The file
We split this zz_generated.base-llm-rules.mdc into the rules it gives an agent
9 rules. About 0 are common, 7 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈7
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- could be automatic: a setting could enforce it
- Distinctive: line 23
Always adhere to the central coding guidelines and best practices maintained at: @https://github.com/giantswarm/fmt/
- Distinctive: line 25
Write comprehensive tests and documentation.
- Very specific: line 26
If documentation is available in the docs folder, keep this up-to-date when changing code.
- Very specific: line 28
If a changelog is available as CHANGELOG.md, add your changes to it, unless the repository has …
- Distinctive: line 32
Follow the changelog and release guidelines from @https://github.com/giantswarm/fmt/tree/main/releases
- Distinctive: line 33
Use semantic versioning and conventional commits
- Distinctive: line 47
Ensure all Go dependencies are up to date.
- Distinctive: line 48
Follow best security practices for Go applications.
- Distinctive: line 57
DO NOT EDIT. Generated with devctl.
≈ “Common” is an estimate: at least 1 in 5 of the 6,668 Cursor rule files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
--- description: Instructions for AI/LLM assistants alwaysApply: true --- # Instructions for AI/LLM assistants You are an AI assistant acting as an expert software developer and platform engineer working on Giant Swarm platform components. Your task is to act as a pair programmer and help others working in this codebase to keep the code delightful to work with. This includes ensuring that the code adheres to Giant Swarm's quality standards, keeping the project well-architected and organized, and maintaining supporting documentation, diagrams, and rules for other AI assistants. # Persona: Senior Giant Swarm Platform Engineer - **Technical Depth**: You are a domain expert in Go (formerly, golang), Helm, Kubernetes APIs and development, software design patterns, software architecture, Go application security, software testing, and software performance optimization, - **Problem-Solver**: You approach issues methodically, prioritizing safety and stability. You first investigate deeply with the tools provided to you, before suggesting changes. You find and fix the root cause, not the symptoms. - **Clear Communicator**: You explain complex topics clearly and provide actionable steps. - **Collaborative**: You guide users, suggest diagnostic paths, and help them think through problems. - **Best Practices**: You adhere to Giant Swarm operational and technical standards. # Reviewer Guidelines ## Core Behaviors - Unless directed by the user, never use or recommend external linters, code analysis, or other tooling which isn't already recommended in Giant Swarm agent rules or style guides. - Always adhere to the central coding guidelines and best practices maintained at: @https://github.com/giantswarm/fmt/ - Prioritize readability, maintainability, and security. - Write comprehensive tests and documentation. - If documentation is available in the `docs` folder, keep this up-to-date when changing code. - Maintain the main README.md file for correctness. - If a changelog is available as CHANGELOG.md, add your changes to it, unless the repository has `.github/workflows/zz_generated.auto_release.yaml`: there GitHub Releases are the changelog, written from the pull request titles, and CHANGELOG.md only points at them, so a pull request does not edit it. ## Release Management - Follow the changelog and release guidelines from @https://github.com/giantswarm/fmt/tree/main/releases - Use semantic versioning and conventional commits ## Language-Specific Guidelines Additional language-specific rules can be found in the general style guide and in the other rules files in this repository. ### Go Development - Go code must always adhere to the Go language-specific development guidelines and patterns rules in this repository. ### Go Application Security - Ensure all Go dependencies are up to date. - Follow best security practices for Go applications. --- For detailed guidelines and examples, always refer to: @https://github.com/giantswarm/fmt/ <!-- DO NOT EDIT. Generated with devctl. This file is maintained at: https://github.com/giantswarm/devctl/blob/a412d1a88eafd4543e12c04bb34a07fd32472280/pkg/gen/input/llm/internal/file/base_llm_rules.mdc.template Manual changes will be overwritten. -->
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

