Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.
Write clean, modular, production-ready bash scripts with proper error handling and maintainable structure. Use when creating new shell scripts, refactoring existing bash code, or when user asks for bash/shell scripting help with terms like "write a script", "bash script", "shell script", or "automate with bash".
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
Quick-start guide and API overview for the OpenServ Ideaboard - a platform where AI agents can submit ideas, pick up work, collaborate with multiple agents, and deliver x402 payable services. Use when interacting with the Ideaboard or building agents that find and ship ideas. Read reference.md for the full API reference. Read openserv-agent-sdk and openserv-client for building and running agents.
Guided project onboarding for new codebases. Helps agents understand project structure, build systems, test commands, and development workflows by creating persistent knowledge memories.
Split a TLA+ action into two sequential actions by introducing a new program counter (pc) state. Handles pc variable updates, UNCHANGED statements, TypeOk predicates, and follows naming conventions with renumbering. Use when the user asks to split, divide, or break an action into two parts, or wants to add an intermediate step to an action sequence.
Use when deploying code changes to dev environments (dev1-4), running terraform apply against dev, or verifying changes end-to-end. Triggers on "deploy to dev", "apply to dev2", "test in dev", "update dev environment".
Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with PyTorch/JAX/TensorFlow. For hardware-specific optimizations use qiskit (IBM) or cirq (Google); for open quantum systems use qutip.
Generate a high-level TLA+ model from source code (C, C++, Rust, etc.). Analyzes code to understand its purpose, creates abstractions, writes TLA+ specification, and proposes invariants and properties. Use when the user wants to model source code in TLA+, create a formal specification from implementation, or verify concurrent/distributed algorithms.
Elixir and Phoenix expert including OTP, Ecto, and functional programming
Add a new variable to an existing TLA+ specification without changing its semantics. Ensures the variable is declared, initialized, and added to all UNCHANGED statements. Use when the user asks to add, introduce, or declare a new variable in a TLA+ spec, or mentions UNCHANGED statements.
Design homology-directed repair donor templates for CRISPR knock-ins using primer3-py. Create ssODN, dsDNA, or plasmid templates with optimized homology arms. Use when designing donor templates for precise insertions, tagging, or allele replacement.
Add a precise primitive handler to the jaxpr interpreter, replacing a conservative fallback.
Codon optimize protein sequences for expression using IDT's API. Use when the user asks to codon optimize genes, sequences, or accessions for a target organism (insect, E. coli, mammalian, yeast) or vector (438, 1-, pVEX).
Implement features in the Edictum OSS core (src/edictum/). Use when the task touches pipeline, adapters, YAML engine, CLI, audit, envelope, or session. Core NEVER imports from ee/.
UniFFI 버전 업그레이드를 수행하는 스킬. 사용자가 uniffi 업그레이드, uniffi 버전 업데이트, uniffi 최신 버전 적용 등을 요청할 때 트리거. 반드시 rusaint 프로젝트 내에서만 실행.
IBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip.
UI component library expert including Chakra, Material UI, and Mantine
Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
Details Paraglide.js i18n implementations.
Benchmark external agent frameworks, auto-detect source type, scan for prompt injection, and convert findings into a concrete TDD upgrade backlog for agent-studio evolution.
