Explore our collection of Agent Skills to enhance your AI workflow.
Applies Kahneman's Dual-Process Theory to optimize decision-making by balancing intuitive responses with deliberate analytical processing.
Implements a rigorous framework for systematic problem analysis, defensible decision-making, and proactive risk assessment.
Analyzes complex systems using Donella Meadows' framework to identify reinforcing loops, balancing loops, and high-impact leverage points.
Automates deterministic end-to-end HTTP testing for ACP-based plugins using JSON-driven specifications.
Validates that project configuration files remain within defined token limits to ensure optimal model performance and context management.
Identifies discrepancies between mental models and reality to improve debugging, architecture, and decision-making accuracy.
Executes a comprehensive suite of validation checks to ensure project integrity and multi-agent system consistency.
Analyzes product development and user needs through the Jobs to Be Done framework to focus on user progress and outcomes.
Optimizes problem-solving by identifying and applying the most effective mental models and critical thinking frameworks for any technical or strategic challenge.
Evaluates technical and business decisions by analyzing the value of foregone alternatives to ensure optimal resource allocation.
Optimizes AI workflows by scanning your local environment and suggesting the most efficient tool combinations for any task.
Identifies high-leverage intervention points in complex systems to maximize impact with minimal engineering effort.
Optimizes React and Next.js applications using Vercel Engineering's performance guidelines to eliminate bottlenecks and minimize bundle sizes.
Clears the Kimchi planning working directory to start fresh while preserving validated project outputs.
Generates, validates, and fixes professional Mermaid diagrams from text-based markup files.
Simplifies the management of Keboola project structures, JSON configurations, and data pipeline transformations.
Prevents invalid data navigation by eliminating self-revisiting paths through non-orientable topological constraints.
Simplifies complex data structure traversal and transformation using bidirectional path compilation and 3-SAT constraint verification.
Integrates the Servo browser engine with ghostty-web to deliver high-performance, full-color terminal tiles using CSS Grid and GPU acceleration.
Implements colored operads and A-infinity structures to ensure mathematically consistent multi-input signal processing pipelines.
Generates pure functional structures and domain-specific languages from functor signatures using Free and Freer monad patterns.
Eliminates self-revisiting paths and topological twists in complex data navigation to ensure deterministic transformations.
Compiles Clojure to LLVM IR with seamless C++ interoperability for high-performance native applications.
Validates and filters data navigation paths using non-orientable topological constraints to prevent infinite cycles and ambiguous traversals.
Analyzes podcast performance data across multiple platforms to provide growth insights and audience metrics.
Models rigorous database schemas by distinguishing entities from attributes to enable category-theoretic data structures and ACSets.
Builds minimal, content-addressed Linux rootfs images using a high-performance Rust reimplementation of the Nix evaluator.
Coordinates multi-agent systems and graph neural networks using sheaf Laplacians for distributed consensus and harmonic inference.
Implements formal model structures and homotopical algebra frameworks for BCI signal chains and topological computing.
Streamlines the creation and management of advanced WezTerm terminal configurations using Lua scripting and real-time documentation.
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