Results for “focus”

当希望提升个人工作效率，实现深度工作，并追求工作与生活的更好平衡时

当需要进入并维持一段高度专注、无干扰的工作状态以处理复杂任务时

当需要系统性地理解、诊断和提升个人专注力，以优化工作效能和生活体验时

Guides daily mindfulness practice to reduce stress, improve focus, and build emotional regulation through structured routines and reflection.

当因“战术压力”或外部紧急事件而处于高压力状态时，需要将这种压力有效转化为极度专注的心流状态，以最高效率推进任务

Transform output-focused roadmaps into outcome-focused ones that communicate strategic intent, rewriting initiatives as outcome statements reflecting user and business impacts.

Audit and fix HTML accessibility issues including ARIA labels, keyboard navigation, focus management, color contrast, and form errors.

Keeps long AI sessions on track by tracking decisions, detecting scope creep, and flagging drift before it costs work.

Defines a time-bounded, focused work session to produce a specific creative or productive output, tracking progress and completion.

Review designs, products, and features using Steve Jobs' standards of ruthless simplicity, focus, and end-to-end excellence.

Guides designing or reviewing Lightning Web Components for keyboard access, semantic labeling, and focus management, prioritizing base components over custom ARIA.

Design, implement, and audit accessible frontend interfaces with a concise checklist for keyboard navigation, ARIA, focus states, and color contrast.

当需要进入高效、创造性的深度工作状态，并将工作体验从“压力”转化为“有挑战的游戏”时

Audits components and pages for WCAG 2.2 AA accessibility issues and applies practical fixes for touch targets, focus states, contrast, labels, and reduced motion.

Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.

Guides implementation of accessible web interfaces to meet WCAG 2.2 AA, WAI-ARIA 1.2, and WCAG2ICT standards, covering semantic HTML, ARIA patterns, focus management, and automated validation.

Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.

当需要进入并维持高度专注的深度工作状态时

当需要系统性地提升工作专注度和生产力，实现高质量成果时

Audits components and pages for WCAG 2.2 AA accessibility issues and applies practical code fixes for touch targets, focus states, contrast, labels, and reduced motion.

Capture friction as methodology notes. Three modes — explicit description, contextual (review recent corrections), session mining (scan transcripts for patterns). Triggers on "/remember", "/remember [description]".

Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.

Trains and fine-tunes vision models for object detection, image classification, and segmentation using Hugging Face Transformers on cloud GPUs, with automatic dataset validation and Hub persistence.

Optimize context usage for the session by reducing bloat, improving token efficiency, and focusing on relevant areas. Use when context is growing large, responses are slow, or switching between unrelated tasks. Covers context analysis, compacting, targeted pruning, MCP-first strategies, and focused scoping by area.

当需要将模糊的长期愿景转化为可执行的日常行动，以提升专注力和生活掌控感时

Use the status-briefing skill to run `pk-reconcile session-start`, then

当需要进入高度专注、高效且愉悦的心流状态以完成创造性或学习性任务时

Pauses mid-conversation to reassess direction, assumptions, and bias, then recommends whether to continue, pivot, or pause.

Generate one high-value follow-up workflow proposal when MoonMind execution quality issues are detected in a run.

RICE feature prioritization with scoring and capacity planning. Usage: /rice prioritize <features.csv> [options]