Explore our collection of Agent Skills to enhance your AI workflow.
Generates deterministic colors with German naming conventions using the SpaltMisch64 algorithm and ternary logic mapping.
Coordinates complex data operations through a 27-agent triadic dispatch system for parallel ACSet access and Goblins vat management.
Automates the creation of Storybook stories and documentation directly from component specifications defined in markdown.
Designs and optimizes high-converting referral programs, affiliate structures, and viral growth loops to turn customers into brand advocates.
Decomposes complex global problems into overlapping local sub-problems using functorial sheaf-theoretic methods.
Implements scalable React component architectures and composition patterns to eliminate prop drilling and boolean proliferation.
Decomposes complex computational problems into three GF(3)-balanced components for optimized parallel execution and sheaf-theoretic gluing.
Maps and analyzes bidirectional observation relationships between agents using sheaf-theoretic consistency and multi-agent awareness graphs.
Coordinates complex, cross-domain debugging investigations by spawning specialized expert agents to identify root causes across full-stack architectures.
Performs deep binary analysis, decompilation, and malware research using industry-standard tools like Ghidra, IDA Pro, and radare2.
Generates comprehensive, INVEST-compliant user stories and microservice-based backlogs from Event Storming results.
Manages settings and preferences for the DevTeam multi-agent automated development workflow.
Verifies mathematical conservation laws and manages autopoietic logic within topological computational frameworks.
Builds scalable, high-performance GitLab CI/CD pipelines using multi-stage workflows, optimized caching, and security scanning.
Enables structured generation and algebraic composition of n-ary operations using colored operads.
Structures Unison language constructs and documentation using algebraic C-set schemas and SPI trajectory tracking.
Reduces Claude Code token waste by generating project-specific MCP configurations that scope tools to the current workspace.
Analyzes binary executables using the angr framework for static analysis, symbolic execution, and vulnerability detection.
Manages project issues with a lightweight, dependency-aware tracker optimized for AI agents and developer workflows.
Automates the capture and analysis of browser console, network, and performance logs to streamline AI-led web application debugging.
Streamlines Svelte development with expert patterns for headless UI libraries, web components, and advanced form handling.
Generates and evolves topological code patterns through autopoietic interaction and color-based seeds.
Prevents agent actions by verifying minimal skill coverage using ε-machine causal state modeling.
Facilitates the creation of decentralized, peer-to-peer applications using the Iroh networking library for Rust.
Powers high-performance categorical geospatial operations using SedonaDB's O(log n) spatial indexing and GeoACSets.jl semantics.
Implements massively parallel functional computation using interaction nets and GPU-accelerated graph reduction.
Optimizes Claude Code knowledge bases by normalizing filenames and merging semantically similar notes using AI.
Automates the migration of codebases and prompts from legacy Claude models to the Opus 4.5 architecture.
Deploys web applications and projects to the Vercel platform with automated framework detection and preview link generation.
Manages complex topological structures and graph-based computational models using category theory principles.
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