[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-106243":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":16,"stars7d":17,"stars30d":17,"stars90d":15,"forks30d":15,"starsTrendScore":18,"compositeScore":19,"rankGlobal":10,"rankLanguage":10,"license":20,"archived":21,"fork":21,"defaultBranch":22,"hasWiki":23,"hasPages":23,"topics":24,"createdAt":10,"pushedAt":39,"updatedAt":40,"readmeContent":41,"aiSummary":10,"trendingCount":15,"starSnapshotCount":15,"syncStatus":13,"lastSyncTime":42,"discoverSource":43},106243,"bioinformatics-agent-skills","ssinder\u002Fbioinformatics-agent-skills","ssinder","Agent Skills for computational biology — RNA-seq, single-cell, protein structure, molecular dynamics, peptide design, literature mining and publication figures. Turn any AI coding agent into a computational biology assistant.","https:\u002F\u002Fssinder.github.io\u002Fbioinformatics-agent-skills\u002F",null,"Python",75,2,63,0,4,6,14,53.03,"MIT License",false,"main",true,[25,26,27,28,29,30,31,32,33,34,35,36,37,38],"agent-skills","agent-skills-standard","bioinformatics","claude-code","claude-skills","computational-biology","literature-mining","molecular-dynamics","peptide-design","protein-structure","research-tools","rna-seq","scientific-visualization","single-cell","2026-10-27 13:53:40","2026-11-02 19:05:45","\u003Cdiv align=\"center\">\n\n\u003Cimg src=\"docs\u002Fassets\u002Flogo.svg\" alt=\"BioinfoAgent Skills\" width=\"348\">\n\n**Turn any AI coding assistant into a computational biologist's research partner**\n\n[![License: MIT](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLicense-MIT-yellow.svg)](LICENSE)\n[![Python](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPython-3.9%2B-blue.svg)](https:\u002F\u002Fwww.python.org\u002F)\n[![Skills](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FSkills-17-brightgreen.svg)](#available-skills)\n[![Agent Skills](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FStandard-Agent_Skills-blueviolet.svg)](https:\u002F\u002Fagentskills.io\u002F)\n[![CI](https:\u002F\u002Fgithub.com\u002Fssinder\u002Fbioinformatics-agent-skills\u002Factions\u002Fworkflows\u002Fskill-spec-validation.yml\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Fssinder\u002Fbioinformatics-agent-skills\u002Factions\u002Fworkflows\u002Fskill-spec-validation.yml)\n[![Tests](https:\u002F\u002Fgithub.com\u002Fssinder\u002Fbioinformatics-agent-skills\u002Factions\u002Fworkflows\u002Ftests.yml\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Fssinder\u002Fbioinformatics-agent-skills\u002Factions\u002Fworkflows\u002Ftests.yml)\n[![Security](https:\u002F\u002Fgithub.com\u002Fssinder\u002Fbioinformatics-agent-skills\u002Factions\u002Fworkflows\u002Fsecurity-scan.yml\u002Fbadge.svg)](https:\u002F\u002Fgithub.com\u002Fssinder\u002Fbioinformatics-agent-skills\u002Factions\u002Fworkflows\u002Fsecurity-scan.yml)\n[![Pages](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDocs-GitHub_Pages-blue.svg)](https:\u002F\u002Fssinder.github.io\u002Fbioinformatics-agent-skills\u002F)\n\n📖 **[Full documentation](https:\u002F\u002Fssinder.github.io\u002Fbioinformatics-agent-skills\u002F)** ——\nquick start, skill catalogue, methodology references, and troubleshooting\n\n\u003C\u002Fdiv>\n\n---\n\n## What is this\n\nA curated collection of **Agent Skills for computational biology**. Every skill is a standardized\n`SKILL.md` package that gives Claude Code, Cursor, Codex, and any other host supporting the\nopen [Agent Skills standard](https:\u002F\u002Fagentskills.io\u002F) **domain expertise, reproducible workflows, and\nvalidation checks** — instead of another generalist that merely knows how to call an API.\n\nCoverage spans transcriptomics, single-cell analysis, protein structure, molecular dynamics, protein\ndocking, inter-chain contact analysis with PyMOL visualization, antimicrobial peptide design, ML\npeptide generation, literature mining, NCBI BioProject metadata, and publication-grade figures.\n\n> Refactored from a private archive of **217 real research scripts** into a discoverable,\n> triggerable, reproducible skill library that follows an open standard. The per-script mapping —\n> what was ported, what was rewritten, and why — is documented in the\n> **[migration map](docs\u002Fmigration-map.md)**.\n\n---\n\n## Why\n\nMost AI assistants can write `scanpy` code. They do not know:\n\n- how much mitochondrial gene percentage to drop from your single-cell data before the filter starts\n  eating real cells\n- why DESeq2's `padj` suddenly came back all `NA` — almost always a mis-specified `design`\n- which flexible loop the first spike in an RMSF curve corresponds to, and what experiment to run on it\n- which of 3,000 retrieved papers are genuinely *target discovery* rather than *functional validation*\n- where to truncate the axes of a reviewer-requested ROC curve so it does not invite criticism\n\n**Those are the things this project carries.** Each skill ships a `references\u002Fmethodology.md`\nrecording the scientific reasoning behind parameter choices, a `references\u002Ftroubleshooting.md`\nrecording root causes for common failures, and a Validation section in `SKILL.md` describing how to\ncheck whether your results are right.\n\n---\n\n## Quick start\n\n### Option 1 — install as Claude Code skills\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002Fssinder\u002Fbioinformatics-agent-skills.git\ncp -r bioinformatics-agent-skills\u002Fskills\u002F* ~\u002F.claude\u002Fskills\u002F\n```\n\nRestart Claude Code and the skills are discovered automatically. Ask it to *\"run a bulk RNA-seq\ndifferential expression analysis\"* and it will load the `bulk-rnaseq` skill on its own.\n\n### Option 2 — use as a Python package\n\n```bash\npip install -e .\nbiopipe --list                      # list every skill\nbiopipe bulk-rnaseq --help         # usage for one skill\n```\n\n### Option 3 — call the scripts directly\n\n```bash\nexport PYTHONPATH=\"$PWD\u002Fpackages\"\n\n# peptide physicochemical properties\npython skills\u002Fpeptide-design\u002Fscripts\u002Fanalyze_peptides.py \\\n    --input peptides.fasta --output results\u002Fpeptide_stats.csv\n\n# ROC curve\npython skills\u002Fscientific-figures\u002Fscripts\u002Fmake_figures.py roc \\\n    --input metrics.csv --output figures\u002Froc.png\n\n# literature search\npython skills\u002Fliterature-search\u002Fscripts\u002Fsearch_literature.py \\\n    --topic \"antimicrobial peptide delivery\" --source pubmed --max-results 50\n```\n\n---\n\n## Available skills\n\n### 🧬 Transcriptomics\n\n| Skill | Description | Key capabilities |\n|------|------|----------|\n| [`bulk-rnaseq`](skills\u002Fbulk-rnaseq\u002F) | RNA-seq quantification and differential expression | FastQC QC · Salmon quantification · DESeq2 differential analysis · GO\u002FKEGG enrichment |\n| [`ena-download`](skills\u002Fena-download\u002F) | ENA raw data download | Portal API FASTQ retrieval · resumable transfers · MD5 verification · metadata export |\n| [`single-cell-rnaseq`](skills\u002Fsingle-cell-rnaseq\u002F) | Standard single-cell RNA-seq workflow | QC filtering · CP10K normalization · HVG · PCA · Leiden clustering · UMAP · cell annotation |\n\n### 🔬 Structural biology\n\n| Skill | Description | Key capabilities |\n|------|------|----------|\n| [`protein-structure`](skills\u002Fprotein-structure\u002F) | PDB structure parsing and secondary structure | Built-in PDB parser · DSSP secondary structure · geometry computation · UniProt metadata |\n| [`protein-interactions`](skills\u002Fprotein-interactions\u002F) | Protein-ligand interactions | PLIP XML parsing · residue-level extraction · interaction networks · PyMOL annotations |\n| [`molecular-dynamics`](skills\u002Fmolecular-dynamics\u002F) | Molecular dynamics simulation and trajectory analysis | RMSD\u002FRMSF\u002FPCA · hydrogen bonds · Ramachandran · trajectory clustering · built-in DCD parser |\n| [`alphafold-db`](skills\u002Falphafold-db\u002F) | AlphaFold DB structure download | API link resolution · batch download · pLDDT confidence filtering · metadata export |\n| [`protein-docking-hdock`](skills\u002Fprotein-docking-hdock\u002F) | HDOCK protein docking | HTTP job submission · Docking Score · confidence formula · model download · queue-status distinction |\n| [`protein-docking-lightdock`](skills\u002Fprotein-docking-lightdock\u002F) | LightDock local protein docking | GSO swarm optimization · DFIRE scoring parsing · best-complex assembly · resumable batch runs |\n| [`pymol-structure-visualization`](skills\u002Fpymol-structure-visualization\u002F) | Inter-chain residue contacts and PyMOL visualization | Grid spatial partitioning · hydrogen bond\u002Fsalt bridge\u002Fhydrophobic\u002Fπ-π\u002Fcation-π classification · hotspot residues · Mermaid network diagrams · PyMOL script generation |\n\n### 🧪 Protein engineering\n\n| Skill | Description | Key capabilities |\n|------|------|----------|\n| [`peptide-design`](skills\u002Fpeptide-design\u002F) | Antimicrobial peptide design and screening | Physicochemical properties · hydrophobicity\u002FpI · stability · MMseqs2 clustering for redundancy removal |\n| [`ml-peptide-generation`](skills\u002Fml-peptide-generation\u002F) | ML peptide generation and screening | PepMLM masked language model · illegal residue filtering · pseudo-perplexity ranking · reproducible seeds |\n\n### 🧬 Cheminformatics\n\n| Skill | Description | Key capabilities |\n|------|------|----------|\n| [`bio-database-fetch`](skills\u002Fbio-database-fetch\u002F) | PubChem compound and taxonomy lookup | PUG-REST batch properties · CAS number extraction · full taxonomy lineage · no browser dependency |\n\n### 📚 Literature mining\n\n| Skill | Description | Key capabilities |\n|------|------|----------|\n| [`literature-search`](skills\u002Fliterature-search\u002F) | Multi-source scholarly literature search | PubMed · OpenAlex · Semantic Scholar · DOI deduplication · RIS\u002FBibTeX export |\n| [`bioproject-search`](skills\u002Fbioproject-search\u002F) | NCBI BioProject metadata retrieval | E-utilities API · title\u002Fdescription\u002Fspecies · keyword filtering · CSV\u002FJSON export |\n| [`paper-fulltext-extract`](skills\u002Fpaper-fulltext-extract\u002F) | Structured full-text extraction from PDFs | GROBID to TEI · section tree\u002Ffigure\u002Freference parsing · JSON\u002FMD\u002FHTML output · corpus search · lead sentences |\n\n### 📊 Scientific visualization\n\n| Skill | Description | Key capabilities |\n|------|------|----------|\n| [`scientific-figures`](skills\u002Fscientific-figures\u002F) | Publication-grade figure generation | ROC · confusion matrices · heatmaps · volcano plots · SHAP summaries · unified publication styling |\n\n---\n\n## Design principles\n\n**Self-contained** — core algorithms ship as pure Python implementations. No scanpy installed? The\nsingle-cell workflow still runs. No OpenMM? DCD trajectories still parse, and RMSD\u002FPCA still compute.\nDependencies are optional; capability is not.\n\n**Reproducible** — fixed random seeds, recorded parameters, pinned versions, and run metadata written\nalongside the results.\n\n**Verifiable** — every skill defines its own quality-control stage, so there is an explicit way to\ncheck whether the output is correct.\n\n**No hardcoded paths** — all paths are parameterized and all output follows a standard directory\nconvention. Not a single `\u002FUsers\u002Fxxx\u002F...` is baked into the code.\n\n**Zero setup** — `pip install -e .` is enough. No cloud services, API keys, or databases to configure.\n\n---\n\n## Layout\n\n```\nbioinformatics-agent-skills\u002F\n├── skills\u002F                    # 17 independently installable skills\n│   ├── bulk-rnaseq\u002F\n│   │   ├── SKILL.md           # trigger description + workflow + validation\n│   │   ├── scripts\u002F           # executable scripts\n│   │   └── references\u002F        # methodology + troubleshooting guide\n│   └── ...\n├── packages\u002F\n│   ├── biopipe_core\u002F          # shared layer: config\u002Flogging\u002FHTTP retry\u002FCLI\u002FIO\n│   └── biopipe\u002F               # unified CLI entry point and skill registry\n├── scripts\u002F\n│   ├── validate_skills.py     # skill spec validator (CI core)\n│   └── init_skill.py          # skill scaffolding generator\n├── tests\u002F                     # unit tests and validator self-tests\n├── docs\u002F                      # usage guides and skill catalogue\n└── .github\u002Fworkflows\u002F         # 7 CI pipelines\n```\n\n---\n\n## Development\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002Fssinder\u002Fbioinformatics-agent-skills.git\ncd bioinformatics-agent-skills\npip install -e \".[dev]\"\n\npython -m pytest tests -v              # run the test suite\npython scripts\u002Fvalidate_skills.py      # validate every skill\npython scripts\u002Fvalidate_skills.py --strict   # treat warnings as failures\n```\n\nSee [CONTRIBUTING.md](CONTRIBUTING.md) before adding a new skill.\n\n### CI pipelines\n\n| Workflow | Purpose |\n|--------|------|\n| `skill-spec-validation` | Validates that every skill conforms to the Agent Skills spec |\n| `script-syntax` | Multi-version Python syntax check + Ruff linting |\n| `tests` | Unit tests + `--help` smoke test for every skill |\n| `security-scan` | Dependency vulnerability audit + hardcoded credential scan |\n| `pr-skill-scan` | Targeted validation and reporting for skills changed in a PR |\n| `pages` | Builds and deploys the documentation site |\n| `release` | Automated release packaging |\n\n---\n\n## Citation\n\nIf you use this project in your research, please cite:\n\n```bibtex\n@software{bioinfoagent2026,\n  title  = {BioinfoAgent Skills: Agent Skills for Computational Biology},\n  author = {sinder},\n  year   = {2026},\n  url    = {https:\u002F\u002Fgithub.com\u002Fssinder\u002Fbioinformatics-agent-skills}\n}\n```\n\nSee [CITATION.cff](CITATION.cff) for details.\n\n---\n\n## Contributing\n\nContributions of new skills, bug fixes, and documentation improvements are welcome. See\n[CONTRIBUTING.md](CONTRIBUTING.md). Read [docs\u002FSKILL_SPEC.md](docs\u002FSKILL_SPEC.md) before submitting a\nnew skill.\n\nParticipation in this project implies agreement with the [Code of Conduct](CODE_OF_CONDUCT.md).\n\n## License\n\nMIT © sinder. See [LICENSE](LICENSE).\n\n## Disclaimer\n\nThis project provides analysis and computation tooling. Its outputs require independent verification\nby the researcher and do not constitute medical, clinical, or regulatory advice.\n\n---\n\n\u003Cdiv align=\"center\">\n\n**[Star this project ★](https:\u002F\u002Fgithub.com\u002Fssinder\u002Fbioinformatics-agent-skills)** — help more\nresearchers discover these reproducible research skills.\n\n\u003C\u002Fdiv>\n","2026-11-03 04:31:25","CREATED_QUERY"]