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bio-consensus-sequences
Generate consensus FASTA sequences by applying VCF variants to a reference using bcftools consensus. Use when creating sample-specific reference sequences or reconstructing haplotypes.
compbio-pi
This skill serves as Lily's personal computational biology PI, empowering Claude to make independent decisions on research project crossroads, covering aspects like topic, model architecture, and experimental design. It handles 80% of medium-level decisions, stress-tests ideas from a Nature reviewer perspective, and refines novelty narratives, reducing the need to consult Lily.
triforce-sync-check
Verify 3-Mirror skill sync consistency across .public/skills, .codex/skills, and .claude/skills. Use after skill changes, before commits, or for CI validation.
terraform-module-library
Build reusable Terraform modules for AWS, Azure, and GCP infrastructure following infrastructure-as-code best practices. Use when creating infrastructure modules, standardizing cloud provisioning, or implementing reusable IaC components.
terraform-infrastructure
Terraform infrastructure as code workflow for provisioning cloud resources, creating reusable modules, and managing infrastructure at scale.
terraform-skill
Terraform infrastructure as code best practices
mcp-integration
Model Context Protocol (MCP) integration specialist. Use when creating
mobile-games
Mobile game development principles. Touch input, battery, performance, app stores.
memory
Manages memory, SSOT files, and Plans.md operations. Use when user mentions メモリ, memory, SSOT, decisions.md, patterns.md, マージ, merge, Plans.md, 移行, migrate. Do NOT load for: 実装作業, レビュー, 一時的なメモ, セッション中の作業記録.
ml-expert
Implements machine learning solutions including model architectures, training pipelines, optimization strategies, and performance improvements. This skill spawns a specialist ML implementation agent.
mobile-games
Mobile game development principles. Touch input, battery, performance, app stores.
modal
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.