Skills.

Give your AI a better way to work.

A skill is a set of written instructions that teaches an AI how to do one job the way it should be done: review a pull request, plan a migration, write the release notes.

Install one here and it travels with your account into Claude, Claude Code, Cursor and every other client you sign in with.

Category: AI & models

9,019 results · page 97 of 301

  • bio-ml-docking-rescoringSkillAI & models

    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 o

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-molecular-descriptorsSkillAI & models

    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 featu

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-molecular-standardizationSkillAI & models

    Standardizes molecular structures using the ChEMBL structure pipeline for normalization and parent selection plus RDKit rdMolStandardize for explicit custom steps such as tautomer canonicalization, salt/solvent stripping, charge handling, stereochemistry handling, mixture selection, and isotope norm

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-outlier-splicing-detectionSkillAI & models

    Detects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q hyperparameter), OUTRIDER (gene-level outlier expression via autoencoder denoising), LeafcutterMD (Dirichlet-mul

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-pileup-generationSkillAI & models

    Generate pileup data for variant calling using samtools mpileup and pysam. Use when preparing data for variant calling, analyzing per-position read data, or calculating allele frequencies.

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-qsar-modelingSkillAI & models

    Builds QSAR / QSPR models using chemprop D-MPNN, MolFormer, Uni-Mol, ChemBERTa, random forest baselines, and Gaussian processes with explicit handling of OECD 5 principles, applicability domain (kNN, leverage, conformal prediction, Mahalanobis), scaffold-balanced splits, ensemble uncertainty, calibr

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-reaction-enumerationSkillAI & models

    Enumerates virtual chemical libraries via reaction SMARTS transformations using RDKit and reaction templates, with explicit handling of atom mapping, RDChiral template extraction, product validation, RECAP/BRICS fragmentation, R-group decomposition, matched molecular pair analysis (MMPA), and Free-W

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-retrosynthesisSkillAI & models

    Performs retrosynthetic planning using AiZynthFinder (template-based MCTS), maintained or version-pinned template-free models, ASKCOS, and emerging RetroSynFormer with explicit handling of route scoring, configurable MCTS rewards, building-block availability, and forward-prediction checks. Use when

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-sashimi-plotsSkillAI & models

    Creates sashimi-style plots showing RNA-seq read coverage and splice junction counts using ggsashimi (general-purpose, condition-grouped overlays), rmats2sashimiplot (rMATS-output-aware), MAJIQ-VOILA (LSV posteriors interactive HTML), leafviz (leafcutter clusters Shiny), Jutils (tool-agnostic heatma

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-scaffold-analysisSkillAI & models

    Analyzes chemical libraries by scaffold using Bemis-Murcko scaffolds, generic frameworks, cyclic skeletons, matched molecular pair (MMP) analysis via mmpdb, R-group decomposition, Free-Wilson analysis, scaffold hopping, and chemotype-aware ML train/test splits. Use when identifying chemotype cluster

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-shape-similaritySkillAI & models

    Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape + color), shape vs ECFP4 complementarity, conformer-ensemble searching, alignment optimization, and scaffold

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-single-cell-splicingSkillAI & models

    Analyzes alternative splicing at single-cell resolution. The first decision is library chemistry — 10X 3' is fundamentally limited (RT primes from poly-A, R2 falls in 3' UTR, <0.1 junction read per cell per AS event). Plate-based full-length methods (Smart-seq3, FLASH-seq, VASA-seq, STORM-seq) and s

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-splice-variant-predictionSkillAI & models

    Predicts whether a DNA variant alters mRNA splicing using sequence-based deep-learning tools — SpliceAI (10kb context dilated CNN, clinical default), Pangolin (multi-tissue), MMSplice (modular per-region CNN with calibrated ΔPSI), SpliceTransformer/TrASPr (tissue-aware transformers), SpliceVault (em

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bio-splicing-quantificationSkillAI & models

    Quantifies alternative splicing as PSI (percent spliced in) from RNA-seq using rMATS-turbo (BAM-based event), SUPPA2 (TPM-based event), MAJIQ V3 (LSV-based Bayesian), leafcutter (annotation-free intron clusters), VAST-TOOLS (cross-species with microexon support), Shiba (junction-imbalance-corrected,

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • bioprobenchSkillAI & models

    Score an LLM's biological-protocol reasoning on the BioProBench benchmark: protocol QA, step ordering, error detection, protocol generation, and LLM-judged error reasoning; or generate the responses.

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • boltzSkillAI & models

    Structure prediction for protein, nucleic-acid, and small-molecule complexes with Boltz-2 (Passaro & Wohlwend et al. 2025, github.com/jwohlwend/boltz). Reach for this skill to validate designed binders against a target, to co-fold a protein with a SMILES or CCD ligand, or to get an open-source Alpha

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • borzoiSkillAI & models

    Predict genome-wide functional tracks (RNA-seq, CAGE, DNase, ChIP) from DNA sequence with Borzoi. Use this skill when: (1) Scoring the regulatory effect of a variant on expression/accessibility, (2) Generating predicted coverage tracks for a locus, (3) Prioritising non-coding variants by predicted t

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • chai1SkillAI & models

    Structure prediction for protein, nucleic-acid, and small-molecule complexes with the Chai-1 foundation model (Chai Discovery 2024, github.com/chaidiscovery/chai-lab). Reach for this skill to predict an antibody-antigen or protein-ligand complex from a single FASTA, to re-fold designed binders as an

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • esmfold2SkillAI & models

    Biohub ESMFold2 / ESMFold2-Fast all-atom co-folding (Candido et al. 2026, github.com/Biohub/esm). Single-sequence and MSA modes; protein, DNA, RNA, ligand (CCD/SMILES), modified residues. FoldBench Ab-Ag 50-55%, PPI 70-77% DockQ-pass. Also covers the ESMC-{300M,600M,6B} protein language models from

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • evo2SkillAI & models

    Score, embed, and generate DNA sequences with Evo 2, a long-context genomic foundation model. Use this skill when: (1) Computing per-nucleotide or per-sequence likelihoods for variant effect scoring, (2) Embedding genomic windows for downstream classification, (3) Generating DNA conditioned on a pre

    Ready to connect★ 409

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  • example_statsSkillAI & models

    descriptive-statistics helpers — summary (mean/std/median), quantile, zscore normalization, and Pearson correlation on plain Python number lists (no pandas/numpy).

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • fair-esm2SkillAI & models

    Embed proteins with Meta AI's ESM-2 (`fair-esm` package). Use this skill when: (1) Extracting per-residue or per-sequence embeddings for downstream ML, (2) Masked-LM likelihood / mutation effect scoring, (3) Contact prediction from a sequence.

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • figure-composerSkillAI & models

    Compose one publication-grade multi-panel figure. Entry from a one-line claim + data refs, OR from an existing figure via `derive_outline(png)`. Runs a per-figure loop: outline (12-col grid, per-panel ask + label_budget) → fan-out one sub-agent per panel (each loads `figure-style`) → tile + stamp le

    Ready to connect★ 409

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  • figure-styleSkillAI & models

    Publication-grade figure correctness and legibility rules. Load before drawing any plot and call `apply_figure_style()` — sets a role-mapped font-size ladder, outward ticks, frameless legends, and 300-dpi output. The skill is a checklist, not a house look: data fidelity (claim-titles tested against

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • indication-dossierSkillAI & models

    Generate a therapeutic indication dossier. Covers the patient population, epidemiology, disease biology, standard of care, regulatory precedent, and landmark clinical trials.

    Ready to connect★ 409

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  • literature-reviewSkillAI & models

    Find, verify, and synthesize scientific literature — from "what's the seminal paper for X" through full multi-source reviews. Covers grounding claims in real retrieved sources, avoiding fabricated citations, handling retractions, and calibrating confidence to evidence strength.

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • mineral_spectra_analysisSkillAI & models

    Raman mineral mixture spectra analysis pipeline for unknown mixed-mineral spectra; preprocess noisy spectra once, iteratively match residual peaks against a reference spectral library, unmix components with NNLS, diagnose reliability, write reports, and optionally generate/evaluate synthetic benchma

    Ready to connect★ 409

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  • openfold3SkillAI & models

    Structure prediction using OpenFold3, an open-weights PyTorch reproduction of AlphaFold3 from the AlQuraishi Lab. Use this skill when predicting protein/nucleic-acid/ligand complex structures with an Apache-2.0-licensed AF3 reimplementation.

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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  • paper-narrativeSkillAI & models

    Judge and reshape the STORY a paper's figures tell. Input is the work itself — manuscript (or abstract) + figure deck — no hand-written brief. `derive_paper_brief(abstract, captions)` extracts pitch/vision/per-figure-claims; a handling-editor reviewer on the full deck returns hook_verdict (would Fig

    Ready to connect★ 409

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  • reaction-atom-mappingSkillAI & models

    Map atoms and changed bonds for a complete reaction with RXNMapper. Use for reactant/product correspondence and reaction-centre audits, not target-only retrosynthesis or feasibility.

    Ready to connect★ 409

    github.com/pku-yuangroup/openai4s381 stars

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What is a skill?

A skill is plain text, usually a SKILL.md file and the scripts it refers to, written for an AI rather than for a person. It carries the steps, the house rules and the examples a good answer needs, so you stop pasting the same briefing into every new chat.

54,764 of the 55,196 skills listed here can be served through ahel today, and they come from public repositories. Each one has its own page with the instructions themselves on it, so you can read what a skill will tell your AI to do before you install it.

Install one and every AI you use gets it

Installing a skill adds it to your gateway and turns it on in the same step. Claude Code surfaces it as a slash command; any client can read the full instructions with the skill_read tool.

Nothing is copied into a project folder. The instructions are served from your account, so the same skill is there in every AI you connect, and turning it off removes it from all of them at once.

See how to connect your AI