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Found 12 Skills
Create beautiful, performant SVG animations and illustrations. Use this skill when the user asks to create SVG graphics, icons, illustrations, animated logos, path animations, morphing shapes, loading spinners, or any animated SVG content. Covers SMIL animations, CSS-driven SVG animation, path drawing effects, shape morphing, motion paths, gradients, masks, and filters.
Provides brand naming frameworks, evaluation criteria, and templates for startup naming work. Auto-activates during brand name development, name evaluation, domain checking, and trademark research. Use when discussing brand name, company name, product name, naming strategy, SMILE SCRATCH framework, domain availability, trademark, name evaluation, sound symbolism, or naming matrix.
Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.
This skill should be used when the user asks to "animate an SVG", "make a line draw itself on", "do a stroke draw-on / signature animation", "morph one shape into another", "move an element along a path", "animate an icon/logo", or "animate an SVG gradient or filter". Covers stroke-dashoffset draw-on, path morphing, motion-along-path, and animated icons/gradients/filters via CSS, SMIL, and GSAP.
Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery: SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
Implied volatility analysis for options via Longbridge — IV vs HV comparison, IV percentile rank, volatility smile and skew, options pricing assessment, strategy selection guidance. Triggers: "隐含波动率", "IV", "期权波动率", "波动率偏斜", "波动率微笑", "HV", "历史波动率", "IV百分位", "期权定价", "隱含波動率", "期權波動率", "波動率偏斜", "波動率微笑", "歷史波動率", "IV百分位", "期權定價", "implied volatility", "IV percentile", "volatility smile", "volatility skew", "HV vs IV", "options pricing", "vol surface", "TSLA.US implied vol".
Model, forecast, and interpret volatility using time-series models and options-implied measures. Use when the user asks about EWMA, GARCH models, implied volatility, volatility surfaces, volatility term structure, or the VIX. Also trigger when users mention 'volatility smile', 'volatility skew', 'realized vs implied vol', 'volatility risk premium', 'vol clustering', 'mean-reverting volatility', 'options pricing inputs', 'RiskMetrics', 'decay factor', or ask how to forecast future volatility for risk management.
Python cheminformatics library for molecular manipulation and analysis. Parse SMILES/SDF/MOL formats, compute descriptors (MW, LogP, TPSA), generate fingerprints (Morgan, MACCS), perform substructure queries with SMARTS, create 2D/3D geometries, calculate similarity, and run chemical reactions.
Open-source cheminformatics and machine learning toolkit for drug discovery, molecular manipulation, and chemical property calculation. RDKit handles SMILES, molecular fingerprints, substructure searching, 3D conformer generation, pharmacophore modeling, and QSAR. Use when working with chemical structures, drug-like properties, molecular similarity, virtual screening, or computational chemistry workflows.
Retrieves chemical compound information from PubChem and ChEMBL with disambiguation, cross-referencing, and quality assessment. Creates comprehensive compound profiles with identifiers, properties, bioactivity, and drug information. Use when users need chemical data, drug information, or mention PubChem CID, ChEMBL ID, SMILES, InChI, or compound names.
Designs and manage customer loyalty programs — points, tiers, rewards, referrals, VIP programs, retention mechanics. Covers strategy, structure, and implementation across Brevo Loyalty, Smile.io, LoyaltyLion, Yotpo, Stamp.me, and custom-built programs. Use when designing a loyalty program, choosing loyalty software, setting up points/tiers/rewards, optimizing member engagement, or measuring program ROI. Do NOT use for affiliate/referral programs with commission payouts (use /sales-affiliate-program), email marketing to loyalty members (use /sales-email-marketing), or checkout optimization (use /sales-checkout). For Brevo-specific help, use /sales-brevo.