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Found 1,867 Skills
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.
Comprehensive structural variant (SV) analysis skill for clinical genomics. Classifies SVs (deletions, duplications, inversions, translocations), assesses pathogenicity using ACMG-adapted criteria, evaluates gene disruption and dosage sensitivity, and provides clinical interpretation with evidence grading. Use when analyzing CNVs, large deletions/duplications, chromosomal rearrangements, or any structural variants requiring clinical interpretation.
Guidance for SPR and BLI binding characterization experiments. Use when: (1) Planning binding kinetics experiments, (2) Troubleshooting poor/no binding signal, (3) Interpreting kinetic data artifacts, (4) Choosing between SPR vs BLI platforms.
Implement VIP (View-Interactor-Presenter) Clean Architecture for iOS apps requiring maximum testability, unidirectional data flow, and protocol-based boundaries. Use when refactoring complex features or building enterprise apps with strict separation of concerns.
Real-time smart money analytics API for Polymarket prediction markets, Hyperliquid perpetual futures, and Meteora Solana LP/AMM pools. 63 endpoints. Pay-per-request via x402 on Solana Mainnet USDC. No API keys.
Run MTHDS methods and interpret results. Use when user says "run this pipeline", "execute the workflow", "execute the method", "test this .mthds file", "try it out", "see the output", "dry run", or wants to execute any MTHDS method bundle and see its output.
Draws 4 Tarot cards using os.urandom() to inject entropy into planning when prompts are vague or underspecified. Interprets the spread to guide next steps. Use when the user is nonchalant, feeling lucky, says 'let fate decide', makes Yu-Gi-Oh references ('heart of the cards'), demonstrates indifference about approach, or says 'try again' on a system with no changes. Also triggers on sufficiently ambiguous prompts where multiple approaches are equally valid.
Provides expert-level analysis and diagnosis for Meta Ads campaigns. Use this skill to interpret performance data, identify root causes of issues, and generate actionable recommendations, with a special focus on correctly handling the 'Breakdown Effect'. Use when the user mentions Meta Ads analysis, campaign diagnosis, ad performance, CPA analysis, ROAS analysis, or asks to analyze exported data from Meta Ads Manager.
Design System Governance Workflow for auditing, refactoring, and syncing enterprise design systems, design tokens, Figma variables, and developer handoff outputs.
Extract structured data from Office documents (DOCX, PPTX, XLSX, HWP, HWPX) using the Polaris AI DataInsight Doc Extract API. Use when the user wants to parse, analyze, or extract text, tables, charts, images, or shapes from document files. Invoke this skill whenever the user mentions extracting content from Word, PowerPoint, Excel, HWP, or HWPX files, wants to parse document structure, needs to convert document data for RAG pipelines, or asks about reading tables, charts, or text from Office-format documents — even if they don't explicitly mention "DataInsight" or "Polaris".
Pricing strategy specialist covering pricing models, value metrics, tier packaging, willingness-to-pay research, pricing pages, and price increase strategy. Use when the user wants help with pricing decisions, packaging plans, setting price points, designing pricing pages, running pricing research, choosing a value metric, raising prices, or optimizing monetization. Also triggers for 'pricing tiers', 'freemium vs trial', 'value metric', 'pricing page', 'willingness to pay', 'van Westendorp', 'annual vs monthly pricing', or 'enterprise pricing'.
Strategic guidance on AI scaling laws, capability trajectories, and building products at the frontier of AI capabilities. Use when users ask about AI scaling trends, capability forecasting, planning AI product development timelines, understanding pretraining vs reinforcement learning phases, interpreting AI benchmark improvements, deciding when to build AI products that don't quite work yet, or strategizing around rapidly advancing AI capabilities. Also triggers for questions about task horizon doubling, Jevons paradox in AI, or how to position products for future model improvements.