What problem does it solve?
Adding support for a new bioinformatics tool to MultiQC requires many coordinated steps: writing a parser, registering search patterns and entry points, adding general stats columns, building plots, writing tests, and passing lint checks. This Skill guides the full implementation so nothing is missed.
Core Features & Use Cases
- End-to-end module workflow: Research the tool, choose single-tool or multi-subtool architecture, build the parser, register in
search_patterns.yaml and pyproject.toml, test, and open a PR.
- Ready-made templates and patterns: Class skeletons, parsing patterns (key-value, JSON), general stats headers, table/bargraph/linegraph plot snippets, and test file templates.
- Pitfall prevention: Enforces required calls like
add_software_version() and write_data_file(), correct use of ModuleNoSamplesFound, human-readable labels, and section alerts.
- Use Case: A
module: new GitHub issue asks to support a new QC tool. Use this Skill to scaffold the module, parse its output format, register it, and pass pytest tests/test_modules_run.py -k "toolname" plus lint checks.
Quick Start
Implement a new MultiQC module for the bioinformatics tool described in issue #XXXX, following the implementation checklist and module structure templates.