Career navigation, ethics compliance, open science, mentorship, lab automation, ML for bio
Designs covalent inhibitors and warheads targeting cysteine (most common, ~98% of covalent drugs), lysine, serine, threonine, tyrosine, and aspartate residues, with explicit handling of warhead reactivity (acrylamide, chloroacetamide, vinyl sulfone, sulfonyl fluoride, fluorosulfate, aldehyde, boronate, nitrile), reversibility (kinact/Ki, t_residence), glutathione (GSH) stability, intrinsic reactivity assays, and covalent docking (DOCKovalent, GOLD, HCovDock). Use when designing covalent inhibitors for targeted covalent inhibition (TCI), KRAS G12C-style approaches, or rationalizing covalent SAR.
Performs ML-based protein-ligand pose prediction and scoring using DiffDock-L (diffusion-based), Boltz-1 / Boltz-2 (foundation model with affinity), Chai-1, AlphaFold3 ligand, EquiBind, TANKBind, NeuralPLexer, and hybrid workflows (DiffDock pose + GNINA rescore + PoseBusters QC). Explicit handling of when ML beats classical docking, when classical beats ML, the PB-invalid pose problem, and rescoring as the standard production hybrid. Use when modern docking is needed: foundation-model ligand-pose prediction, AI rescoring of classical poses, or scaffold-hopping in cross-docking scenarios.
Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda window scheduling, soft-core potentials, REST2 enhanced sampling, MBAR/BAR analysis, and cycle closure validation. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.
Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.
Calculates molecular fingerprints (ECFP/Morgan, FCFP, MACCS, RDKit, AtomPair, TopologicalTorsion, Avalon, MAP4, MHFP6) and physicochemical descriptors (Lipinski, QED, TPSA, Crippen LogP, 3D shape) with explicit choice tables, bit vs count semantics, and partial-charge model selection. Use when featurizing molecules for similarity, QSAR, virtual screening, or ML, or selecting the correct fingerprint for a chemotype-aware task.
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A curated collection of research-domain skills for AI agents. Authored by Pradyumna Jayaram, 2026.
open-research-skills (ORS) is a comprehensive skill library for AI agents working alongside researchers, academics, graduate students, postdocs, and R&D engineers. It covers the full lifecycle of research:
literature search → experimental design → analysis → writing → publication → grant writing → mentorship → ethics
18 categories, 118 skills — see INDEX.md for the per-skill table.
| Category | Skills | Description |
|---|---|---|
bioinformatics-sequence | 23 | FASTA/FASTQ/BAM/VCF, alignment, QC, Biopython |
chemoinformatics | 19 | RDKit, ADMET, virtual screening, retrosynthesis, generative design |
research-grants | 9 | NIH R01/K, NSF, ERC, fellowships, foundations, DARPA |
lab-automation | 6 | Opentrons/PyLabRobot, ELNs (eLabFTW/Chemotion/openBIS) |
career-navigation | 6 | Academic CV, tenure, industry transition, interview prep |
scientific-communication | 5 | Talks, posters, podcasts, press releases, elevator pitch |
open-science | 5 | FAIR data, preprints, preregistration, code release, licensing |
scientific-writing | 5 | Manuscript structure, cover letters, rebuttals, AI disclosure |
scientific-thinking | 5 | Brainstorming, critical thinking, hypothesis generation, perspective tour, failure handling |
scientific-visualization | 5 | Figure design, schematics, slides, posters, color & accessibility |
literature-research | 5 | Literature search, systematic review, citation management, paper lookup |
mentorship-teaching | 4 | Onboarding, goal setting, syllabus, course design |
image-analysis-microscopy | 4 | CellProfiler, QuPath, ImageJ/Fiji, best practices |
machine-learning-bio | 4 | Protein LMs, DL for genomics, AlphaFold, scRNA-seq DL |
ethics-compliance | 4 | IRB protocols, data privacy, AI disclosure, image integrity |
peer-review | 4 | Manuscript review, grant review, scholar evaluation, reviewer response |
humanizer-skills | 4 | Scientific voice, AI disclosure, text humanizing, AI detection awareness |
data-engineering | 1 | Snakemake pipeline management |
/plugin marketplace add pradyumnasagar/open-research-skills
/plugin install ors-research@pradyumnasagar
/plugin install ors-bioinformatics@pradyumnasagar
/plugin install ors-career-ethics@pradyumnasagar
Then in a chat:
> Use the bwa-alignment skill to align these reads to GRCh38.
git clone https://github.com/pradyumnasagar/open-research-skills.git
cd open-research-skills
claude
In the chat, reference skills by name. The agent reads the relevant SKILL.md from skills/.
See examples/api-integration.md for Python, TypeScript, AWS Bedrock, and Google Vertex examples.
open-research-skills/
├── README.md # this file
├── LICENSE # MIT
├── AGENTS.md # agent/contributor guide
├── CONTRIBUTING.md # alias for GitHub "Contribute" button
├── CHANGELOG.md # release notes
├── ROADMAP.md # what's done, what's next
├── INDEX.md # per-skill table
├── SCHEMA.md # legacy frontmatter spec (see spec/skill-format.md)
├── TAXONOMY.md # legacy taxonomy (see spec/category-taxonomy.md)
├── THIRD_PARTY_NOTICES.md # upstream attributions
│
├── .claude-plugin/
│ └── marketplace.json # Claude Code plugin marketplace manifest
│
├── spec/ # ORS specification
│ ├── README.md
│ ├── skill-format.md # frontmatter spec
│ └── category-taxonomy.md # 18 categories
│
├── template/
│ └── SKILL.md # template for new skills
│
├── examples/ # worked examples
│ ├── README.md
│ ├── claude-code-installation.md
│ ├── api-integration.md
│ └── multi-skill-workflow.md
│
├── scripts/ # repo automation
│ ├── README.md
│ ├── validate-skills.py
│ └── build-index.py
│
├── tests/ # test suite
│ └── ...
│
└── skills/ # all 118 skills, organized in 18 categories
├── AGENTS.md # skill-authoring guide
├── bioinformatics-sequence/ (23 skills)
├── chemoinformatics/ (19 skills)
├── research-grants/ (9 skills)
└── ... (15 more categories)
---
name: <kebab-case-slug>
description: <one or two sentences — what & when>
license: MIT # optional
---
<!-- metadata: (optional) -->
# Skill Title
> Tagline
## When to use
## Workflow
## Code patterns
## Pitfalls
## Validation
## References
npx claudepluginhub pradyumnasagar/open-research-skills --plugin ors-researchA growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.
Comprehensive feature development workflow with specialized agents for codebase exploration, architecture design, and quality review
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques
Harness-native ECC operator layer - 67 agents, 271 skills, 92 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
UI/UX design intelligence. 67 styles, 161 palettes, 57 font pairings, 25 charts, 15 stacks (React, Next.js, Vue, Svelte, Astro, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui, Nuxt, Jetpack Compose). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, mobile app. Elements: button, modal, navbar, sidebar, card, table, form, chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, flat design. Topics: color palette, accessibility, animation, layout, typography, font pairing, spacing, hover, shadow, gradient.
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.