claude_global

Run shell commands bare — no decorative echo headers ("=== X ==="), no echo-then-cmd chains, no trailing "echo done". Use the Bash tool's description field for any narration. Triggers any time you're about to issue a Bash command.

Expert guide for managing Claude Code global skills and commands. Use when creating new skills, symlinking to projects, updating existing skills, or organizing the centralized skill repository.

Token optimization best practices for cost-effective Claude Code usage. Automatically applies efficient file reading, command execution, and output handling strategies. Includes model selection guidance (Opus for learning, Sonnet for development/debugging). Prefers bash commands over reading files.

BioBlend and Planemo expertise for Galaxy workflow automation. Galaxy API usage, workflow invocation, status checking, error handling, batch processing, and dataset management. Essential for any Galaxy automation project.

Expert in Galaxy tool wrapper development, XML schemas, Planemo testing, and best practices for creating Galaxy tools

Expert in Galaxy workflow development, testing, and IWC best practices. Create, validate, and optimize .ga workflows following Intergalactic Workflow Commission standards.

Maintain per-workflow developer logs in Obsidian when working on Galaxy workflows. Use whenever creating, version-bumping, fixing, or updating an IWC/Galaxy `.ga` workflow or its `-tests.yml`. Logs detailed changes, test YAML edits, and `planemo` invocation history so the correct planemo command (full `planemo test` vs fast `workflow_test_on_invocation`) is obvious without guessing. Triggers on any session that edits `.ga`, edits `-tests.yml`, runs `planemo test`/`planemo workflow_test_on_invocation`, or prepares an IWC PR.

VGP assembly pipeline - Galaxy workflow selection, execution patterns, QC checkpoints, and batch orchestration

Best practices for data aggregation, recalculation, and category management in scientific analyses. Covers when to recalculate vs reuse aggregated data, handling category changes, and ensuring analytical accuracy.

Best practices for creating clear, accurate scientific visualizations with matplotlib, seaborn, and other Python plotting libraries. Covers common pitfalls, optimization techniques, publication-quality figure generation, and Claude API image size constraints.

Organize research project documentation - structure working files, prepare sharing packages, maintain clean project layout

Best practices for creating comprehensive Jupyter notebook data analyses with statistical rigor, outlier handling, and publication-quality visualizations. Includes Claude API image size helpers.

Best practices for iterative refinement of publication-quality scientific figures. Covers systematic improvement workflows, layout optimization, and ensuring all figure elements are publication-ready.

Core bioinformatics concepts including SAM/BAM format, AGP genome assembly format, sequencing technologies (Hi-C, HiFi, Illumina), quality metrics, and common data processing patterns. Essential for debugging alignment, filtering, pairing issues, and AGP coordinate validation.

Phylogenetic tree analysis, visualization, annotation management, and iTOL troubleshooting

Publication-quality bioinformatics figures - phylogenetic trees, genome browsers, iTOL datasets, and data presentation

Best practices for using Claude Code in team environments. Covers skill management, knowledge capture, version control, and collaborative workflows.

Best practices for session documentation - incremental summaries, fix reports, and audit trails

Structured 4-phase debugging methodology. Use when encountering any bug, test failure, unexpected behavior, or pipeline error — before proposing fixes. Enforces root cause investigation first.

Enforces evidence-based completion claims. Use before claiming work is done, tests pass, or bugs are fixed. Requires running verification commands and confirming output before any success claims.

HackMD collaborative markdown - slide presentations, embedded SVG diagrams, and real-time editing best practices

Prepare organized packages of project files for sharing at different levels - from summary PDFs to fully reproducible archives. Creates copies with cleaned notebooks, documentation, and appropriate file selection. After creating sharing package, all work continues in the main project directory.

Unified Python interface to 40+ bioinformatics services (UniProt, KEGG, ChEMBL, Reactome, PSICQUIC). Best for cross-database analysis, ID mapping, and multi-service workflows. For quick single-database lookups use gget.

Fast CLI/Python queries to 20+ bioinformatics databases. Gene info, BLAST, AlphaFold structures, enrichment analysis, single-cell data, disease associations. Best for interactive exploration and quick lookups. For batch/multi-database Python workflows use bioservices.

Query gnomAD (Genome Aggregation Database) for population allele frequencies, variant constraint scores (pLI, LOEUF), and loss-of-function intolerance via GraphQL API. Essential for variant pathogenicity interpretation, rare disease genetics, and identifying loss-of-function intolerant genes.

Expert in Galaxy Training Network (GTN) tutorial development. GTN markdown syntax, special boxes, tool references, snippets, YAML front matter, and best practices for writing and updating training materials in the galaxyproject/training-material repository.

Smart automated backup system with skill integration. Detects project type (notebooks, data files, HackMD docs) and applies appropriate cleanup before backup. Rolling daily backups, compressed milestones, and CHANGELOG tracking.

Best practices for organizing project folders, file naming conventions, and directory structure standards for research and development projects

Best practices for managing development environments including Python venv and conda. Always check environment status before installations and confirm with user before proceeding.

Integration with Obsidian vault for managing notes, tasks, and knowledge when working with Claude. Supports adding notes, creating tasks, and organizing project documentation. Updated with 2025-2026 best practices including MOCs, properties, practical organization patterns, and Obsidian CLI (1.12+).

Access and navigate GenomeArk AWS S3 bucket - VGP assemblies, QC data, and species directory structure

Expert in building and testing conda/bioconda recipes, including recipe creation, linting, dependency management, and debugging common build errors