Results for “lightning-experience”

Builds memory-safe, performant Lightning Web Components with correct lifecycle hook usage, covering build, review, and troubleshooting workflows.

Routes to 82 Lightning Web Components skill packages covering reactivity, wire adapters, component communication, accessibility, performance, security, and Jest testing. Finds and opens the exact skill package for LWC-related requests.

Builds a custom LWC lookup component with typeahead search via Apex SOSL/SOQL, debounce, keyboard navigation, and pill UI for cases where standard pickers fall short.

Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), and distributed training (DDP, FSDP, DeepSpeed) for scalable neural network training.

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

Design, implement, budget, and verify readable real-time game visual effects: particles, smoke/fog, lightning, fire, trails, impacts, bloom/glow, and layered spell timelines. Use when a user needs a VFX spec, lifecycle, engine handoff, particle pooling, effect composition, reduce-motion fallback, or frame-budget diagnosis. Triggers on: game VFX, spell effects, particle system, impact burst, procedural lightning, smoke, bloom, magic aura, or VFX performance.

Organizes PyTorch code with a Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks, and minimal boilerplate. Scales from laptop to supercomputer with the same code.

Guides secure design and review of Lightning Web Components, covering DOM safety, Apex data exposure, and Lightning Web Security.

当遭遇挫折、失败或结果不如预期时，用于将负面经验转化为成长燃料

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

Use Light DOM in LWC when third-party libraries or global CSS require document-level access, with guidance on scoped styles and managed-package constraints.

Runs throwaway experiments to validate feasibility, compare approaches, and surface unknowns before committing to a real build.

Enforce quality, security, and accessibility standards for Salesforce Lightning Web Components, Aura components, and Visualforce pages.

Throwaway experiments to validate an idea before build.

Implements sibling communication between Lightning Web Components using Lightning Message Service (LMS) or the legacy pubsub utility, covering message channel definition, publish/subscribe patterns, and scope selection.

Internal harness probe for the OI-3 readability-guidance spike. Use only when explicitly told to invoke spike-probe. Verifies that a freshly-created project skill renders into a subagent's context via the Skill tool.

Throwaway experiments to validate an idea before build.

Approach an app, tool, codebase, website, or product as a genuine first-time user with zero insider context — try it out using only the information provided, get confused where a real newcomer would, and surface the "obvious" questions that people who built or use the thing daily can no longer see. Use this whenever the user wants a first-time-user test, a fresh perspective, a naive walkthrough, a cold read of their README/onboarding/docs/UI, or says things like "pretend you've never seen this", "would a new user get this?", "test my app like a beginner", "what would confuse someone new?", or "give me fresh eyes on this". Also use it when someone wants to find gaps in onboarding, docs, or first-run experience — even if they don't say "fresh eyes" explicitly.

Run STORM phase 1 — multi-perspective research. This skill should be used when the user asks to "research a topic for an article", "find sources on X from multiple perspectives", "do storm research on X", or invokes /storm:research. Discovers personas, runs simulated Q&A per persona in parallel, and produces an information table + deduplicated sources.

Runs focused experiments to validate feasibility of an idea, saving artifacts to .planning/spikes/ and supporting both idea and frontier modes.

Turn owner feedback about agent behavior into concrete system changes. Use when the owner says something is off, wants the assistant to improve how it operates, asks for a reflection, or wants a durable fix instead of a one-off apology.

Build accessible modal dialogs in LWC using the LightningModal base class, covering open(), close(), sizes, and accessibility.

Forces unrelated concepts together to spark novel solutions and emergent properties.

当意识到自己处于长期迷茫、缺乏动力阶段，需要系统性方法走出困境时

Designs and improves onboarding flows, empty states, and first-run experiences to help users reach value quickly. Use when the user mentions onboarding, first-time users, empty states, activation, getting started, or new user flows.

Run throwaway prototypes to validate feasibility, compare approaches, and report a verdict.

Render long lists (1k+ rows) efficiently in Salesforce LWC using lightning-datatable infinite loading or an IntersectionObserver sentinel, with keyset pagination and accessibility guidance.

OI-3 spike harness — heavy consumer skill, BASELINE arm. Builds an incident post-mortem and sources the readability standard mid-workflow by reading a file directly, with NO Skill-tool call. Use only when explicitly invoked by the spike harness with a TRIAL_ID and data path.

Throwaway experiments to validate an idea before build.

Rehearse

Forces unrelated concepts together to spark novel solutions and uncover emergent properties.

Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.

当意识到自己处于迷茫、例行公事或心流等不同生活状态，并希望主动管理而非被动承受时

Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.

当需要在日常任务或长期目标中创造高度专注、高效且愉悦的“心流”体验时