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copilot-instructions

**Crustchan 2** is a 4chan-style imageboard built for 2026 with a cloud-native architecture. This is an early-stage project (pre-release) that will serve as a successor to the original unfinished Crustchan. **Current Status**: Planning and architectural phase.

Install / Use

npx skills add devhax-heavy-industries/crustchan

Installs into whichever agent you are using.

About this skill
🔧

.clinerules

Cline rules

Quality Score

59/100

Supported Platforms

Cline

Our assessment of copilot-instructions

copilot-instructions scores 59/100 on our quality scale, 4113th of 4,617 Development & Engineering skills we index.

Its .clinerules is 5.2 KB long, well organised into 17 sections and no code examples: a solid amount of guidance for an agent.

It has no GitHub stars yet, so there is no community track record; judge it on its content.

Substance
26/30
Structure
13/20
Description
15/15
Adoption
0/20
Freshness
5/15

Maintenance, license and trust

  • We could not determine when the repository was last updated.
  • Our last check on 2026-10-18 found the source still online.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 68/100, with 3 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

copilot-instructions compared with similar skills

All 4 of these similar skills score higher than copilot-instructions; compare them before choosing.

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LocalAIby mudler10050.2ktodayMCP Server

Frequently asked questions

How do I install copilot-instructions?
Run npx skills add devhax-heavy-industries/crustchan. The install tabs above show the steps for each supported agent.
Which AI agents does copilot-instructions work with?
It is written for Cline, as a .clinerules file. Other agents that read the same format can often use it too.
Is copilot-instructions safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 68/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is copilot-instructions still maintained?
We could not determine when the repository was last updated.

Instructions for Crustchan 2

Project Overview

Crustchan 2 is a 4chan-style imageboard built for 2026 with a cloud-native architecture. This is an early-stage project (pre-release) that will serve as a successor to the original unfinished Crustchan.

Current Status: Planning and architectural phase. The codebase structure described in AGENTS_manual.md reflects planned architecture, not current implementation. Expect incomplete, broken, or placeholder code.

Architecture

Stack

  • Backend: Rust 1.93.1 (Axum framework with OpenAPI 3 support)
  • Frontend: TypeScript, React, Tuono
  • Package Management: pnpm (monorepo)
  • Orchestration: Turborepo (planned)
  • Authentication: OAuth2 + OIDC (Apple, Microsoft, Google, Twitch, Facebook)
  • Database: PostgreSQL
  • Caching/Events: Redis or KV store (potentially RabbitMQ for events)

Planned Structure

The monorepo will contain:

  • apps/api/ - Rust backend using Axum
  • apps/frontend/ - React TypeScript frontend
  • apps/serverless/ - Rust serverless components
  • packages/ - Shared packages
  • tests/ - Integration and E2E tests

Key Design Decisions

  • RDBMS over NoSQL: Postgres instead of DynamoDB for better transactional consistency
  • Cloud-Agnostic: Avoids AWS-specific services; suitable for deployment to personal infrastructure
  • CQRS Pattern: Read replicas or Redis for separating read/write concerns
  • Planned Future: AI-assisted development, image optimization (WebP), admin/user UIs, OAuth2 sign-up

Setup & Development

Note: The project is not currently set up for development. When infrastructure is in place, look for:

  • pnpm install - Install dependencies (when pnpm-workspace.yaml is configured)
  • pnpm build - Build all packages (when turbo.json is configured)
  • pnpm test - Run all tests
  • Backend tests: cargo test (from apps/api/)
  • Frontend tests: jest (from apps/frontend/)

Key Conventions

Documentation Structure

  • .github/instructions/ - Detailed best practices for specific tools and languages (Rust, Docker, GitHub Actions, Markdown)
  • .github/agents/ - Specialized agent configurations for different roles (React engineer, GitHub Actions expert, etc.)
  • .github/skills/ - Reusable skills for agents (PRD generation, agent configuration)
  • AGENTS_manual.md - High-level tech stack and planned project structure
  • README.md - Project overview and vision

Rust Development

  • Follow conventions in .github/instructions/rust.instructions.md
  • Use cargo fmt for formatting and cargo clippy for linting
  • Implement comprehensive error handling with Result<T, E>
  • Prefer borrowing over cloning; use Arc<T> for thread-safe shared ownership
  • Write rustdoc comments (///) for all public APIs

Frontend Development

  • TypeScript with React for type safety
  • Use ESLint/Prettier as configured by .github/instructions/
  • Follow accessibility and React patterns detailed in agent instructions
  • Use jest for testing

Markdown & Documentation

  • Follow guidelines in .github/instructions/markdown.instructions.md
  • All docs should have clear structure with H2/H3 headings
  • Use code blocks with language specification
  • Keep line length under 400 characters

Docker & Containerization

  • Multi-stage builds for efficiency
  • Use minimal base images (alpine, slim, distroless)
  • Non-root users in containers
  • See .github/instructions/containerization-docker-best-practices.instructions.md

CI/CD & GitHub Actions

  • Comprehensive guidance in .github/instructions/github-actions-ci-cd-best-practices.instructions.md
  • Use least privilege for GITHUB_TOKEN permissions
  • Leverage OIDC for cloud authentication (avoid long-lived secrets)
  • Implement comprehensive testing strategy (unit, integration, E2E)

Reference Documents

When working on specific areas, consult:

| Area | Document | |------|----------| | Rust best practices | .github/instructions/rust.instructions.md | | Docker/containerization | .github/instructions/containerization-docker-best-practices.instructions.md | | GitHub Actions workflows | .github/instructions/github-actions-ci-cd-best-practices.instructions.md | | Markdown documentation | .github/instructions/markdown.instructions.md | | HTML/CSS styling | .github/instructions/html-css-style-color-guide.instructions.md | | Product requirements | .github/PRD.md (when created) | | React expertise | .github/agents/expert-react-frontend-engineer.agent.md |

Development Workflow

  1. Create issues first - All work should be tracked in GitHub issues
  2. Follow naming conventions - Check existing code for patterns (see Rust and Markdown instructions)
  3. Run tests before committing - Both Rust (cargo test) and frontend (jest)
  4. Document public APIs - Use rustdoc for Rust, JSDoc for TypeScript
  5. Use specialized agents - Leverage .github/agents/ when working on specific domains

Important Notes

  • Early stage: Code may be incomplete or non-functional
  • AI-assisted development: This project uses AI agents intentionally; review and test their outputs carefully
  • No AWS: Infrastructure should be cloud-agnostic (deploy to personal servers, Portainer, etc.)
  • Avoid slop: Maintain code quality standards despite automated assistance

Related Skills

View on GitHub
GitHub Stars0
CategoryDevelopment
UpdatedNaNy ago
Forks0

Trust signals

68/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

2 medium1 low