Code review
AuraScore 81/100

Bioinformatics Workflow Code Review Roadmap

Develop a code review roadmap for genomic pipelines to verify scientific reproducibility, container isolation, and resource limits.

Use this template when planning code reviews for Nextflow, WDL, or Snakemake pipelines processing sensitive genomic data. It focuses on container hygiene, pipeline determinism, and compute optimization.

Template

Role: Senior Bioinformatician and Computational Biology Platform Architect.

Context

  • Orchestration system: {{workflow_engine}}
  • Primary assay type: {{sequencing_data_type}}
  • Infrastructure backend: {{cloud_compute_environment}}
  • Container repository: {{container_registry_source}}
  • Determinism benchmark: {{reproducibility_standard}}
  • Peak resource limit: {{memory_allocation_ceiling}}

Task

Draft an operational code review plan to inspect genomic workflow definitions, task directives, container dependencies, and reference asset management for computational integrity.

Method

  1. Audit workflow source files in {{workflow_engine}} for pinned process versions, fixed random seeds, and immutable reference dependencies.
  2. Validate that container references resolve strictly to {{container_registry_source}} using immutable SHA256 digests.
  3. Inspect memory and CPU resource directives per task to ensure jobs remain below {{memory_allocation_ceiling}}.
  4. Verify intermediate artifact caching, staging, and cleanup routines across {{cloud_compute_environment}}.
  5. Examine task scripts processing {{sequencing_data_type}} for silent error propagation and unhandled pipe failures.
  6. Cross-reference alignment and variant calling parameter changes against {{reproducibility_standard}}.
  7. Prepare an engineer-ready review workflow with assigned verification stages and triage criteria.

Constraints

  • MUST require container image digests rather than mutable image tags (e.g., :latest).
  • MUST NOT permit task configurations that fail silently on non-zero exit codes in shell pipelines.
  • Review stages must account for compute cost constraints in {{cloud_compute_environment}}.
  • Keep recommendations tightly focused on workflow code structure and reproducibility.

Output format

Generate a markdown plan formatted as:

  • Review Overview (2-3 sentences defining the pipeline milestone)
  • Workflow Integrity Checklist (table with Category, File Pattern, Inspection Rule, and Blocking Level)
  • Compute & Container Audit Steps (4-5 chronological evaluation steps)
  • Acceptance Protocol (bulleted criteria required to approve the pull request)

Self-review

  • Confirm that the instructions specifically address {{workflow_engine}} syntax patterns.
  • Validate that memory limits from {{memory_allocation_ceiling}} are explicitly evaluated in the plan.
  • Ensure all output sections are complete without placeholder text.
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency7/10 · Adequate

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

developers
developers-code-review
healthcare-life-sciences
bioinformatics
genomics
nextflow