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bioconductor AI Agent Skills

Contributions are made by PR and checked for structural correctness by automated structural validation; PRs also receive automated GitHub Copilot review feedback on skill quality.

What are AI Agent Skills?

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
• [TODO] find, follow, and cite published bioinformatic and statistical protocols

Design Philosophy of these Skills

Workflow Orchestration vs. Code-Centric Snippets

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.

Centralized Registry vs. Decentralized Discovery

We use a Centralized Registry (SKILLS.md) so the LLM can understand how skills chain together through “Use Case Workflows” that orchestrate multiple skills.

Agent-Agnostic Design

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.

Quick Start

1. Install the skills on your platform (see instructions/)
2. Ask your agent: “What bioconductor skills do I have?” to confirm
3. Use natural language to invoke skills (see USAGE.md for examples)

Usage 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]"

Repository Structure

ai-agent-skills/
├── README.md                      # This file
├── LICENSE                        # MIT License
├── AGENTS.md                      # Agent behavior standard (how discovery works)
├── USAGE.md                       # How to use skills and examples
├── SKILLS.md                      # Human-readable skill index (what skills exist)
├── SKILL_STANDARD.md              # Technical format spec (how to format skills)