Explore our collection of Agent Skills to enhance your AI workflow.
Automates browser interactions, UI testing, and visual verification using the Playwright framework.
Synchronizes multi-agent workflows by blocking execution until specific messages or acknowledgments arrive on specified topics.
Systematically tracks and optimizes the specialization of AI agents within workflows to improve performance and reusability.
Organizes and structures Personal Knowledge Management vaults using the Linking Your Thinking methodology and automated analysis scripts.
Configures Inngest in TypeScript projects to enable event-driven architecture and reliable background workflows.
Generates high-quality AI images and videos from text prompts and visual assets using the Jimeng multi-modal engine.
Automates computational pathology workflows by processing whole-slide images and multiparametric data for machine learning analysis.
Streamlines the creation of high-quality technical documentation through empirically validated templates and automated quality checks.
Generates high-quality visual content from text descriptions and image references using the Gemini API.
Designs and implements robust event-driven architectures using standardized Inngest event patterns and schemas.
Optimizes Inngest function execution using concurrency limits, throttling, rate limiting, and advanced event batching strategies.
Provides AI-ready drug discovery datasets, standardized benchmarks, and molecular oracles for therapeutic machine learning.
Performs advanced time series machine learning tasks including classification, forecasting, and anomaly detection using the specialized Aeon toolkit.
Implements robust cross-cutting concerns like logging, encryption, and dependency injection for Inngest serverless functions.
Provides comprehensive guidance and implementation patterns for explaining machine learning model predictions using SHAP values.
Builds fault-tolerant, long-running background workflows using Inngest's durable execution model.
Accelerates methodology convergence in AI workflows by reducing iteration cycles through structural optimization and metric-based planning.
Accesses 20+ genomic databases for rapid bioinformatics queries, sequence analysis, and protein structure prediction.
Provides standardized architectural patterns and best practices for building sophisticated terminal user interfaces with Bubbletea v2.
Refactors complex Go codebases using automated metrics and standardized protocols to reduce technical debt.
Automates full-featured browser interactions, web testing, and data extraction using Chrome Canary.
Systematizes project testing with coverage-driven gap closure and automated pattern generation to reach 80%+ code coverage.
Facilitates machine learning on genomic interval data, including embeddings for BED files and single-cell ATAC-seq analysis.
Provides advanced protein language model capabilities for sequence generation, structure prediction, and functional design using ESM3 and ESM C.
Implements seamless client-side page transitions and state management for Webflow sites using Taxi.js.
Implements robust Python features using a strict test-driven development methodology with pytest and FastAPI integration.
Compares vulnerability reports between two OCI container images to identify fixed and newly introduced security issues.
Generates detailed, agent-executable Product Requirements Documents (PRDs) by analyzing repository context and clarifying feature goals through interactive questioning.
Deploys applications to Render by analyzing codebases, generating Blueprints, and managing cloud infrastructure.
Manages custom code behavior between Webflow's Designer mode and the published site to ensure a seamless editing experience.
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