🏠 Home | 🎯 Skills Index | ⚙️ Installation | 🤖 Agent Behavior | 📋 Skill Standards
This is a repository of "Skills" intended to make AI coding agents (Claude Code, GitHub Copilot, Antigravity, Mistral, Aider, etc etc) perform more effectively and in alignment with community standards and best practices for Bioconductor users and developers. Its contents are written by humans and AI and vetted for accuracy and adherence to coding and analysis standards by human Bioinformaticians from the Bioconductor community.
Each "Skill" provides structured, Markdown-formatted instructions that teach AI agents about topics including
- Package structures and conventions
- Analysis workflows and best practices
- Data types and their handling
- Testing and documentation standards
- Bioconductor-wide patterns
With these skills, AI agents can:
- Create new skills and index them in SKILLS.md
- Follow Bioconductor coding standards
- Analyze R code and packages for security, efficiency, and code quality, and suggest improvements
- Adhere to preferred bioinformatic workflows and statistical methods
These skills provide Workflow/Process Orchestration rather than simple code snippets. They define the intent, the multi-step workflow, and the domain knowledge required. This approach enables high autonomy and allows the AI to adapt to different project structures using its general reasoning capabilities.
The Role of Code Snippets as Guardrails: Code snippets serve as guardrails within a broader workflow. Use them specifically for highly specific APIs, standardized methodologies, or overcoming LLM anti-patterns. Use workflows for the "what" and "why", and embed code snippets for the "how" only when exact syntax is required.
We use a Centralized Registry (SKILLS.md) so the LLM can understand how skills chain together through "Use Case Workflows" that orchestrate multiple skills.
Skills in this repository are agent-agnostic by design. They work across multiple AI agents through natural language invocation.
See AGENTS.md for detailed requirements and SKILL_STANDARD.md for technical format details.
- Install the skills on your platform (see instructions/)
- Ask your agent: "What bioconductor skills do I have?" to confirm
- Use natural language to invoke skills (see SKILLS.md for examples)
Create AI Instructions for an R Package:
"Create .github/instructions for this R package"
Analyze an R Package:
"Analyze this R package"
Create a New Skill:
"Help me create a new skill for [purpose]"
ai-agent-skills/
├── README.md # This file
├── LICENSE # MIT License
├── AGENTS.md # Agent behavior standard (how discovery works)
├── SKILLS.md # Human-readable skill index (what skills exist)
├── SKILL_STANDARD.md # Technical format spec (how to format skills)
├── CONTRIBUTING.md # Contribution guidelines
├── CHANGELOG.md # Version history and release notes
│
├── skills/ # All skills (flat structure)
│ ├── {skill-name}/ # Each skill in its own directory
│ │ ├── SKILL.md # Skill documentation (required)
│ │ └── templates/ # Optional supporting files
│ └── ... (see SKILLS.md for complete list)
│
└── instructions/ # Platform adapters (thin wrappers)
├── README.md # Adapter purpose and requirements
├── claude.md # Claude Code setup and shortcuts
├── copilot.md # GitHub Copilot setup and shortcuts
└── antigravity.md # Google Antigravity setup
We welcome contributions! See CONTRIBUTING.md for guidelines.
- Issues: Report bugs or request features via GitHub Issues
- Discussions: Ask questions in GitHub Discussions
MIT License - see LICENSE for details.
These skills are developed and maintained by the Bioconductor Agentic AI working group to make AI agents more efficient at developing and applying Bioconductor code.