What problem does it solve? Writing Snakemake rules that follow consistent project conventions is error-prone: missing log directives, wrong relative paths, conda env naming collisions, and cluster failures that are hard to diagnose. This Skill encodes the project's rule-writing standards so every new or edited rule is correct and testable before cluster submission. ## Core Features & Use Cases - Convention-Compliant Rule Generation: Creates rules with mandatory log: directives, stdout/stderr redirection, correct code/-relative paths, conda env references, and mem_mb/threads resource settings. - Pre-Submission Testing Workflow: Enforces a three-step local validation process (verify conda env imports, run the script on the smallest sample, target a single output) before submitting all samples to Slurm. - Cluster Failure Debugging: Diagnoses Slurm errors including OOM kills, missing sbatch in PATH, shadow-prefix permission errors, and unexpected re-runs caused by log directive changes. - Use Case: You need to add a rule that counts reads per sample from BAM files. The Skill generates the rule with proper wildcards, logging, and conda env, then walks you through testing it on one small sample before scaling to the full dataset. ## Quick Start Ask the AI to add a new Snakemake rule in code/rules/ that processes your input files, following the project conventions for logging and conda environments.
