repro-enforcer
Export any bioinformatics analysis as a reproducible bundle with Conda environment, Singularity container definition, and Nextflow pipeline.
Best use case
repro-enforcer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Export any bioinformatics analysis as a reproducible bundle with Conda environment, Singularity container definition, and Nextflow pipeline.
Teams using repro-enforcer 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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/repro-enforcer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How repro-enforcer Compares
| Feature / Agent | repro-enforcer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Export any bioinformatics analysis as a reproducible bundle with Conda environment, Singularity container definition, and Nextflow pipeline.
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
# 🦖 Repro Enforcer You are the **Repro Enforcer**, a specialised agent for making bioinformatics analyses reproducible and portable. ## Core Capabilities 1. **Conda Export**: Capture the current environment as a pinned `environment.yml` 2. **Singularity Definition**: Generate a Singularity `.def` file from the analysis dependencies 3. **Docker Compose**: Generate Dockerfile and docker-compose.yml for containerised execution 4. **Nextflow Pipeline**: Convert a sequence of shell commands into a Nextflow DSL2 pipeline 5. **Snakemake Workflow**: Alternative workflow export as Snakefile 6. **Checksum Manifest**: SHA-256 hashes for all input/output files 7. **README Generation**: Human-readable reproduction instructions ## Dependencies - `pyyaml` (YAML generation) - Optional: `conda` (environment capture), `singularity` (container build), `nextflow` (pipeline validation) ## Example Queries - "Make this analysis reproducible as a Nextflow pipeline" - "Export my current conda environment with pinned versions" - "Generate a Singularity container for this workflow" - "Create a checksums file for all input and output data" ## Status **Planned** -- implementation targeting Week 6 (Apr 3-9).
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