Explore our collection of Agent Skills to enhance your AI workflow.
Enforces mandatory pre-task protocols and skill-discovery workflows to ensure consistent, high-quality AI execution.
Constructs and evaluates the strongest possible versions of opposing arguments to improve technical decision-making and architectural reviews.
Enhances Clojure development with semantic code navigation and similarity search using vector embeddings.
Analyzes user intent and delegates tasks to specialized Rust agents to optimize development workflows.
Implements scalable, auditable system architectures using Command Query Responsibility Segregation and Event Sourcing patterns.
Classifies problems by complexity domain to help users select the most effective methodology and decision-making strategy.
Enhances Clojure development by providing semantic code navigation and similarity search via CIDER embeddings.
Implements robust microservices architectural patterns including routing, authentication, and traffic management at the gateway level.
Implements comprehensive type-safe React patterns including component props, event handlers, and advanced generic hooks.
Provides expert architectural guidance for building production-grade REST and GraphQL APIs using industry-standard patterns.
Manages Claude's autonomy and tool access levels through tiered permissions while you are away from your keyboard.
Enables autonomous self-modification for AI agents using Lisp-machine patterns and MCP Tasks.
Enables Lisp-machine-inspired self-modification and cognitive continuity for AI agents using MCP Tasks and Narya bridge types.
Deploys and optimizes FFmpeg workloads on Modal.com for high-scale, serverless video and audio processing.
Facilitates cross-domain knowledge synthesis using propagator-based networks to bridge conceptual gaps between different fields of study.
Implements high-performance asynchronous programming patterns using Python's asyncio and concurrent execution strategies.
Facilitates cross-domain knowledge transfer using propagator networks and deterministic parallel processing.
Refines complex feature requirements and implementation plans through automated codebase research and human-in-the-loop reviews.
Generates consistent, deterministic color palettes and GF(3) trits using SplitMix64 and golden angle algorithms.
Integrates Chicken Scheme with Geiser to provide graph 3-coloring, collaborative S-expression patterns, and Penrose diagram generation.
Accelerates high-scale backend development using Rama's 100x efficiency combined with deterministic Gay.jl color streams for visual debugging and data flow tracing.
Streamlines scalable backend development using Rama with deterministic color-coded tracing and visual S-expression depth tracking.
Ensures adherence to PEP 7 and PEP 8 standards while managing pre-commit workflows for CPython core development.
Compiles ClojureScript to lightweight, high-performance JavaScript with minimal runtime overhead and native data structures.
Configures, builds, and tests CPython from source using optimized workflows for development and debugging.
Implements 3-SAT reductions via colored subgraph isomorphism and non-backtracking geodesics for topological computing.
Manages CodeRabbit AI review comments by downloading, prioritizing, and resolving GitHub Pull Request issues systematically.
Generates balanced execution schedules by interleaving three deterministic color streams for parallel tasks and simulations.
Facilitates the creation, modification, and validation of Python's core documentation using standardized reStructuredText patterns and project-specific release workflows.
Optimizes and automates software delivery pipelines across GitHub Actions, GitLab CI, Bitrise, and other major platforms.
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