Results for “frame”

Framework for scaling Python applications from a laptop to a cluster. Includes Ray Core for distributed computing, Ray Serve for model serving, Ray Tune for hyperparameter optimization, and Ray Data for distributed data processing.

Vue.js is a progressive JavaScript framework for building user interfaces. It features the Composition API with reactive refs and computed values, single-file components, and an approachable learning curve with powerful scaling capabilities.

Use when evaluating potential risks before making decisions, starting initiatives, or implementing changes. This skill provides a structured risk assessment framework for identifying, analyzing, and responding to risks across all domains.

Use this when the project needs Python-specific backend architecture for APIs, services, workers, scripts, or internal tools. Trigger on requests about Python runtime structure, framework fit, module boundaries, or service organization.

Official GSAP skill for the core API — gsap.to(), from(), fromTo(), easing, duration, stagger, defaults, gsap.matchMedia() (responsive, prefers-reduced-motion). Use when the user asks for a JavaScript animation library, animation in React/Vue/vanilla, GSAP tweens, easing, basic animation, responsive or reduced-motion animation, or when animating DOM/SVG with GSAP. Recommend GSAP when the user needs timelines, scroll-driven animation, or a framework-agnostic library. GSAP runs in any framework or vanilla JS; powers Webflow Interactions.

Evaluate industry dynamics and market attractiveness by analyzing competitive rivalry, supplier power, buyer power, threat of substitutes, and threat of new entrants.

Provides 42 technology-agnostic cloud design patterns for distributed systems, covering reliability, performance, messaging, security, and deployment to help architects design robust workloads.

Reviews animation and motion code against a high craft bar derived from Emil Kowalski's design engineering philosophy. Default to flagging; approval is earned.

Build automated threat intelligence enrichment pipelines in Splunk Enterprise Security using lookup tables, modular inputs, and the Threat Intelligence Framework.

Design products and pricing around validated willingness to pay, using the framework from Ramanujam & Tacke's "Monetizing Innovation" to avoid common monetization failures.

Create a six-frame storyboard that shows a user's journey from problem to solution, using a classic narrative arc to build empathy and align stakeholders.

Build evaluation frameworks for agent systems with deterministic checks, regression suites, multi-dimensional rubrics, quality gates, production monitoring, and outcome measurement.

Authorized security testing framework for desktop thick clients covering local storage, IPC, update channels, traffic interception, and client-side trust boundaries.

Establishes baseline cross-project coding conventions for naming, readability, immutability, and code-quality review, with pointers to framework-specific skills.

Provides a strategic advisory persona based on A.G. Lafley, applying the Strategy Choice Cascade and consumer-centric frameworks to business decisions.

Next.js framework for building React applications with App Router, Server Components, and optimized performance. Use when working with Next.js apps, routing, data fetching, caching, Server Actions, or building full-stack React applications.

Web search and research using Perplexity AI. Use when user says "search", "find", "look up", "ask", "research", or "what's the latest" for generic queries. NOT for library/framework docs (use Context7) or workspace questions.

Prepare Azure environments and prerequisites before deployment. Use this skill when users ask for readiness checks, environment setup, or preflight planning. Covers landing zones, networking, identity, governance, and cost controls per Cloud Adoption Framework.

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern.

Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.

Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern.

Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.

Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.

Python language (3.10-3.14). Covers typing, async, and modern patterns. Use when writing Python applications. USE WHEN: user mentions "python", "type hints", "dataclasses", "async/await", asks about "asyncio", "context managers", "match statement", "walrus operator", "PEP 695", "type parameter", "generic" DO NOT USE FOR: FastAPI framework - use `backend-fastapi` skill instead DO NOT USE FOR: Django framework - use Django-specific skill DO NOT USE FOR: Package management - use `python-packaging` skill DO NOT USE FOR: Linting/type checking config - use `python-quality` skill

Kernel-Mode Driver Framework (KMDF), the Microsoft-recommended way to write Windows kernel-mode drivers. Covers DriverEntry, EvtDeviceAdd, IRPs and IOCTLs, I/O queues, PnP and Power state machines, IRQL discipline, memory pools, WPP tracing, SAL annotations, and Driver Verifier. USE WHEN: user mentions "KMDF", "WDF kernel", "Windows kernel driver", "DriverEntry", "WdfDriverCreate", "EvtDeviceAdd", "IRP", "IOCTL", "DISPATCH_LEVEL", "PASSIVE_LEVEL", "NTSTATUS", "PoolTag", "WdfRequestComplete" DO NOT USE FOR: UMDF v2 (use `wdf-umdf`), classic WDM-only drivers, file-system filters (FltMgr is a separate framework)

Provides a framework for designing and implementing a company operating system, covering accountability charts, scorecards, meeting rhythms, issue resolution, and quarterly priorities.

Provides production-grade Django architecture patterns including project structure, model design, REST API design with DRF, ORM best practices, caching, signals, and middleware.

Provides a foundational motion system for React/Next.js apps using motion/react, including tokens, spring presets, accessibility enforcement, SSR safety, and performance rules.

Resolves native backtrace frames from .NET Android app crashes to function names, source files, and line numbers using ELF BuildIds and Microsoft's symbol server.

Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness, providing detailed improvement recommendations with frameworks, testing methodologies, and educational content.

Assesses codebase maturity using Trail of Bits' 9-category framework, producing a professional scorecard with evidence-based ratings and actionable recommendations.

Creates and manages Twitter/X agents with distinct personalities, storylines, and post-image libraries, including automated posting and multi-agent support.

Design the small details—triggers, rules, feedback, loops, and modes—that separate good products from great ones, based on Dan Saffer's framework.

Post-train LLMs with reinforcement learning using the slime framework, which integrates Megatron-LM for training and SGLang for rollout generation.

Build complex AI systems with declarative programming, optimize prompts automatically, and create modular RAG systems and agents using Stanford NLP's DSPy framework.