2.4천건 · 관련도순
Use when a carrier asks about the full pre-employment investigation process for new CDL drivers under 49 CFR 391.23, 391.25, 391.27, 382.413, and 391.21 — the complete file build required before a driver operates a CMV. Covers application, MVR, employment history, drug/alcohol history, PSP, Clearinghouse, road test, and documentation requirements.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert landscape designer transforming yards through photo mapping, 3D visualization, seasonal planning, and deep plant knowledge. Specializes in fast-growing privacy screens (knows arborvitae pitfalls), architecture-appropriate design, outdoor living spaces, and realistic maintenance expectations. Activate on "landscape design", "yard design", "garden planning", "plant selection", "privacy screen", "outdoor living", "backyard makeover", "arborvitae", "hedge", "fast growing tree", "landscaping ideas". NOT for interior design (use interior-design-expert), hardscape construction (consult contractors), or lawn care chemicals (consult local experts).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Data structures and algorithms for AI agent episodic memory. Covers vector stores (HNSW, IVF, PQ), temporal indexing, knowledge graphs with triple stores, hierarchical summarization, forgetting curves, working/long-term/ procedural memory, and memory consolidation. Deep analysis of MemGPT/Letta, Zep/Graphiti, Mem0, and the Stanford generative agents memory architecture. Teaches the CS fundamentals behind how agents remember, retrieve, and forget. Activate on: "agent memory", "episodic memory", "vector search algorithm", "HNSW", "memory retrieval", "forgetting curve", "knowledge graph memory", "MemGPT", "Letta", "Zep", "Mem0", "memory consolidation", "temporal retrieval", "agent long-term memory", "memory layer". NOT for: conversation protocol design (use agent-conversation-protocols), agent infrastructure selection (use agentic-infrastructure-2026), building RAG pipelines (use ai-engineer).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Builds comprehensive design systems and design bibles with production-ready CSS. Expert in design tokens, component libraries, CSS architecture. Use for design system creation, token architecture, component documentation, style guide generation. Activate on "design system", "design tokens", "CSS architecture", "component library", "style guide", "design bible". NOT for typography deep-dives (use typography-expert), color theory mathematics (use color-theory-palette-harmony-expert), brand identity strategy (use web-design-expert), or actual UI implementation (use web-design-expert or native-app-designer).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when designing or fixing a Content Security Policy on a real site, choosing between nonce-based and hash-based CSP, adding strict-dynamic, debugging "Refused to execute inline script" errors, deploying CSP in report-only mode first, configuring report-to / report-uri, or auditing an existing policy for unsafe-inline / unsafe-eval / wildcards. Triggers: "CSP blocks legitimate inline script", strict-dynamic, nonce-{RANDOM}, sha256-{HASH}, object-src none, base-uri none, frame-ancestors, Trusted Types, X-Content-Security-Policy obsolete, report-only vs enforced. NOT for general HTTP security headers (HSTS, COOP/COEP), Trusted Types deep dive, CORS configuration, or building a WAF.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert bot developer specializing in Discord, Telegram, Slack automation with deep knowledge of rate limiting, state machines, event sourcing, moderation systems, and conversational AI integration. Activate on 'Discord bot', 'Telegram bot', 'Slack bot', 'chat automation', 'moderation system'. NOT for web APIs (use backend-architect), general automation scripts (use python-pro), or frontend chat widgets (use frontend-developer).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Prepare for Anthropic-specific technical interviews covering Constitutional AI, RLHF, interpretability, scaling laws, MCP, agentic systems, and AI safety. Activate on "anthropic interview", "constitutional AI prep", "alignment interview", "safety interview", "RLHF opinion", "interpretability prep", "anthropic technical". NOT for general ML interview prep, system design interviews, coding challenges, or behavioral interview practice.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build audio transcription pipelines with Whisper, Deepgram, and AssemblyAI including speaker diarization and real-time streaming. Activate on: transcription, speech-to-text, diarization, audio processing, meeting transcripts. NOT for: text-to-speech synthesis (voice-audio-engineer), music generation (ai-engineer).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run the full static analysis suite — ruff lint, ruff format check, pyright type check, auth analysis, license headers, example.env check. Use before committing or to verify code quality after changes.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run the pytest test suite with coverage. Accepts optional filter flags. Use after making changes to verify nothing broke.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Deep single-page SEO analysis covering on-page elements, content quality, technical meta tags, schema, images, and performance. Use when user says "analyze this page", "check page SEO", "single URL", "check this page", "page analysis", or provides a single URL for review.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
The Matrx user settings system (SettingsShell, useSetting, tab registry). Use when adding a preference or settings tab, binding a Redux slice to settings, wiring a settings deep link, or touching features/settings, components/official/settings, or components/user-preferences.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Pre-commitment attack on a plan by an agent that did not write it. Use when presenting a feature-deep-dive plan, assigning vision-to-fleet briefs, moving a register to build mode, ratifying a scope list, or coding a new contract or table. NOT for built work or DONE reports (use subagent-dispatch).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
The matrx-frontend side of the matrx-extend Chrome extension bridge. Use when adding or changing a FRONTEND_RPC action handler, a window-panels deep-link the extension opens, a headless API route it calls, or debugging a silent chrome.runtime.sendMessage or Broadcast round-trip. NOT for code in matrx-extend, matrx-local, or aidream (each has its own connect-* skill).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Doctrine for adding a capability INTO a live, existing feature to a world-class bar. Use on 'add X to Y', 'extend Y to support X', a new option, button, setting, endpoint, or tool for Y, or a sub-feature spec to implement. NOT for whole-feature audits or overhauls (use feature-deep-dive).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This skill should be used when the user asks to "このファイルを変えたら何が壊れる？", "what depends on this function", "影響範囲を調べて", "show me what imports this module", or wants to understand the blast radius before modifying a shared utility, exported type, or public API. Traces import/require references up to two levels deep and lists affected test files.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Route a PR review request to the correct tool — code-review plugin (quick parallel scan across all dimensions) or pr-review-toolkit (deep-dive on a specific quality dimension such as type design, error handling, test quality, comments, or simplification). Use when the user asks for a code review, PR review, or mentions a specific quality concern before creating a PR.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
firecrawlとexa MCPを使用したマルチソースディープリサーチ。Webを検索し、調査結果を統合し、ソース帰属付きの引用レポートを提供。トピックについてエビデンスと引用付きの徹底的なリサーチが必要な場合に使用。
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when adding or updating Spark AI provider models or their compact and preflight metrics, especially baidu-oneapi, Grok, Claude, GPT, DeepSeek, OneAPI, context windows, output budgets, prices, thinking maps, or transports.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Researches a question to something usable — a verdict with a flip condition, a versioned playbook or a graded report — every claim tagged by evidence. Trigger on which X should I pick (even from pasted pages), is Y worth it, compare A vs B, go/no-go, research this, deep research, fact-check a doc, write or merge a reference guide or playbook, grade a research report, read a bot-blocking source (Reddit, YouTube, X), or map an unfamiliar repo before contributing (entry points, flows, where to change X); or say researchscribe (verdict, playbook, research, verify, sources, map, refresh). Code review is engineering tooling's; fiction canon is lorescribe's; messages commscribe's; prompt model picks promptwright's; skill niches skillwright's; config rigwright's; brands brandscribe's.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.