snakemake-workflow-manager

Snakemake workflow management skill for rule-based pipeline execution

509 stars

Best use case

snakemake-workflow-manager is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Snakemake workflow management skill for rule-based pipeline execution

Teams using snakemake-workflow-manager should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/snakemake-workflow-manager/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/bioinformatics/skills/snakemake-workflow-manager/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/snakemake-workflow-manager/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How snakemake-workflow-manager Compares

Feature / Agentsnakemake-workflow-managerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Snakemake workflow management skill for rule-based pipeline execution

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Snakemake Workflow Manager Skill

## Purpose
Enable Snakemake workflow management for rule-based pipeline execution.

## Capabilities
- DAG-based workflow execution
- Cluster/cloud execution
- Conda environment management
- Checkpointing and resume
- Benchmark collection
- Report generation

## Usage Guidelines
- Define rules with clear inputs/outputs
- Use Conda for environment management
- Configure for cluster execution
- Enable checkpointing for large workflows
- Collect benchmarks for optimization
- Generate workflow reports

## Dependencies
- Snakemake
- Conda
- Bioconda

## Process Integration
- Reproducible Research Workflow (reproducible-research)
- Analysis Pipeline Validation (pipeline-validation)

Related Skills

plugin-registry-manager

509
from a5c-ai/babysitter

Manage SDK plugin discovery and registration

deprecation-manager

509
from a5c-ai/babysitter

Manage API and SDK deprecation lifecycle

api-key-manager

509
from a5c-ai/babysitter

API key generation, rotation, and management system

clinical-workflow-analysis

509
from a5c-ai/babysitter

Analyze clinical workflows to identify inefficiencies, bottlenecks, and improvement opportunities using Lean healthcare principles and value stream mapping techniques

zotero-reference-manager

509
from a5c-ai/babysitter

Reference management for bibliography organization, annotation sync, and citation formatting

osf-workflow-integrator

509
from a5c-ai/babysitter

Skill for integrating with Open Science Framework workflows

data-versioning-manager

509
from a5c-ai/babysitter

Skill for managing data versions and provenance

nanosensor-calibration-manager

509
from a5c-ai/babysitter

Nanosensor characterization skill for calibration, sensitivity analysis, and selectivity validation

nanomaterial-lims-manager

509
from a5c-ai/babysitter

Laboratory Information Management System skill for nanomaterial sample tracking and data management

ligand-exchange-protocol-manager

509
from a5c-ai/babysitter

Surface chemistry skill for managing ligand exchange reactions, bioconjugation protocols, and functional group quantification

cleanroom-protocol-manager

509
from a5c-ai/babysitter

Cleanroom operations skill for managing protocols, contamination control, and process flows

characterization-workflow-orchestrator

509
from a5c-ai/babysitter

Workflow automation skill for orchestrating multi-technique characterization sequences