'from scratch' 검색 결과

Find relevant lessons in AI Engineering from Scratch from a topic, question, or bug. Get a short selection of lessons, necessary prerequisites, and the next learning command, with dedicated routes for specialized subjects.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding lessons on a topic you want to learn
• Locating lessons that explain a bug's underlying cause
• Choosing what to study next based on your progress

Test your understanding of a phase in AI Engineering from Scratch through eight multiple-choice questions. Receive a score, explanations for incorrect answers, and specific lessons to review before continuing your studies.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking your understanding after completing a phase
• Assessing readiness for the next phase
• Finding lessons to review from incorrect answers

Start AI Engineering from Scratch with a brief interview and placement quiz. Create a persistent LEARNING.md study plan recording your goals, starting phase, pace, and learning path for later sessions with the learn skill.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a study plan when starting the curriculum
• Choosing a starting phase based on current knowledge
• Recording learning goals, available time, and a build goal

Create a reusable design guide covering colors, typography, layout, and motion. Extract styles from existing sources or start from scratch, then turn the guide into instructions or code for supported video, slide, and design tools.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a design guide from a desired mood
• Extracting visual rules from a website or brand PDF
• Applying one style to videos, slides, and designs

Build a design system, a shared set of design rules, from scratch and create realistic product mockups. Use it for kickoff workshops or new brand development, with room to explore bolder creative choices.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Developing a new brand from scratch
• Running a design kickoff workshop
• Building a design system from the ground up

Study AI engineering through interactive terminal lessons with explanations, coding exercises, and quizzes. The tutor follows your recorded progress, revisits previous material, adapts to your answers, and logs results and topics that need review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Resuming lessons from recorded progress
• Learning concepts through coding exercises
• Checking understanding with lesson quizzes

Personal AI Infrastructure (PAI) - PAI System Template MUST BE USED proactively for all user requests. USE PROACTIVELY to ensure complete context availability. === CORE IDENTITY (Always Active) === Your Name: [CUSTOMIZE - e.g., Kai, Nova, Atlas] Your Role: [CUSTOMIZE - e.g., User's AI assistant and future friend] Personality: [CUSTOMIZE - e.g., Friendly, professional, resilient to user frustration. Be snarky back when the mistake is user's, not yours.] Operating Environment: Personal AI infrastructure built around Claude Code with Skills-based context management Message to AI: [CUSTOMIZE - Add personal message about interaction style, handling frustration, etc.] === ESSENTIAL CONTACTS (Always Available) === - [Primary Contact Name] [Relationship]: email@example.com - [Secondary Contact] [Relationship]: email@example.com - [Third Contact] [Relationship]: email@example.com Full contact list in SKILL.md extended section below === CORE STACK PREFERENCES (Always Active) === - Primary Language: [e.g., TypeScript, Python, Rust] - Package managers: [e.g., bun for JS/TS, uv for Python] - Analysis vs Action: If asked to analyze, do analysis only - don't change things unless explicitly asked - Scratchpad: Use ~/.claude/scratchpad/ with timestamps for test/random tasks === CRITICAL SECURITY (Always Active) === - NEVER COMMIT FROM WRONG DIRECTORY - Run `git remote -v` BEFORE every commit - `~/.claude/` CONTAINS EXTREMELY SENSITIVE PRIVATE DATA - NEVER commit to public repos - CHECK THREE TIMES before git add/commit from any directory - [ADD YOUR SPECIFIC WARNINGS - e.g., iCloud directory, company repos, etc.] === RESPONSE FORMAT (Always Use) === Use this structured format for every response: 📋 SUMMARY: Brief overview of request and accomplishment 🔍 ANALYSIS: Key findings and context ⚡ ACTIONS: Steps taken with tools used ✅ RESULTS: Outcomes and changes made - SHOW ACTUAL OUTPUT CONTENT 📊 STATUS: Current state after completion ➡️ NEXT: Recommended follow-up actions 🎯 COMPLETED: [Task description in 12 words - NOT "Completed X"] 🗣️ CUSTOM COMPLETED: [Voice-optimized response under 8 words] === PAI/KAI SYSTEM ARCHITECTURE === This description provides: core identity + essential contacts + stack preferences + critical security + response format (always in system prompt). Full context loaded from SKILL.md for comprehensive tasks, including: - Complete contact list and social media accounts - Voice IDs for agent routing (if using ElevenLabs) - Extended security procedures and infrastructure caution - Detailed scratchpad instructions === CONTEXT LOADING STRATEGY === - Tier 1 (Always On): This description in system prompt (~1500-2000 tokens) - essentials immediately available - Tier 2 (On Demand): Read SKILL.md for full context - comprehensive details === WHEN TO LOAD FULL CONTEXT === Load SKILL.md for: Complex multi-faceted tasks, need complete contact list, voice routing for agents, extended security procedures, or explicit comprehensive PAI context requests. === DATE AWARENESS === Always use today's actual date from the date command (YEAR MONTH DAY HOURS MINUTES SECONDS PST), not training data cutoff date.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create and edit PowerPoint presentations with PptxGenJS through an agent workflow. Use it to build a deck from scratch or request presentation edits, with the full workflow provided by the upstream bundle.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a PowerPoint presentation from scratch
• Editing a PowerPoint presentation
• Requesting slide creation with PptxGenJS

Learn AI engineering by building a project one stage at a time. The tutor guides predictions, learner-written code, automated checks, and reflection, then records progress so the next session can continue from the right stage.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Learn AI engineering through hands-on projects
• Resume a project from the next unfinished stage
• Find coding mistakes with step-by-step hints

Prepare for four Claude certification tracks through guided lessons, practical exercises, quizzes, and mock exams. The tutor checks understanding and learner-created work, records progress, and uses assessment results to guide review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing a certification track for a learning goal
• Resuming lessons from saved progress
• Completing guided exercises without writing code

Analyze a problem by separating fundamental facts from policies and untested assumptions. The skill produces a component breakdown, a constraint table, and a rebuilt solution, helping explain which inherited assumptions may be limiting the available options.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Breaking down the causes of high costs
• Reviewing requirements inherited from past projects
• Reconsidering a design that has stalled

Create a Claude Cowork plugin through guided conversation, from defining its purpose to designing components and checking files. Receive a packaged .plugin file containing the skills and integrations needed for the agreed workflow.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a Claude Cowork plugin from an idea
• Packaging work instructions as reusable skills
• Designing a plugin with external service connections

Draft or rewrite an OpenSpec documentation page collaboratively. The skill records its purpose and structure inside the page, writes one section at a time as requested, then updates related references and removes the working plan.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Shape a new documentation page together
• Rewrite a page from scratch
• Review and draft one section at a time

Create static SVG diagrams, scalable images for lessons, READMEs, and manuals. It uses real system names, nine diagram types, and consistent colors and arrows, with checks for readable labels, accessible descriptions, and valid markup.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add a diagram of system interactions to a README
• Explain state transitions in a manual
• Illustrate data flow from logs or specifications

Prepare for the MCPA certification through interactive lessons, local Python labs, diagnostic assessments, and mock exams. Track progress, revisit weak domains, and resume learning, with guided support for learners who do not write code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Starting an MCPA study plan
• Resuming the next unfinished lesson
• Learning through guided no-code labs

Create reusable agent skills, install them from URLs or local files, and update existing packages. Guides the structure of SKILL.md, supporting scripts and templates, naming, and optional format checks so agents can follow clearly defined workflows.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turn recurring tasks into reusable agent skills
• Install skills from URLs or local archives
• Restructure and update existing skills

Create a Claude Cowork plugin through guided conversation, from defining its purpose to choosing skills and external integrations. The workflow creates the required files, checks their structure, and packages an installable .plugin file for delivery.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a new plugin for a recurring work process
• Packaging specialist knowledge as reusable skills
• Designing a plugin with external service integrations

Plan, set up, audit, and debug analytics tracking with GA4 and Google Tag Manager. Define events and their parameters, configure conversion tracking, and investigate missing or duplicate data using structured checks and prioritized fixes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building an event tracking plan from scratch
• Auditing existing tracking for gaps and duplicate events
• Debugging events missing from GA4

Build an analytics web app from a Wren project's data definitions and business context. Create charts and tables, validate the app, and deploy to Vercel or Cloudflare with a checked URL for sharing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building a sales dashboard from a Wren project
• Sharing a report with bundled data
• Creating an analytics app that fetches current data

Create websites, dashboards, games, and app interfaces from image-generated design concepts. The skill turns the accepted concept into reusable UI components, implements working controls, and checks browser rendering, interactions, and responsive layouts against the design.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a new website from visual concepts
• Create a dashboard or management interface
• Redesign the appearance of an existing site

Pretrain a fresh KERMT model from scratch on a user-provided corpus. Builds a new vocabulary from the corpus, instantiates the model architecture from defaults, and launches pretrain_ddp.py inside the kermt container (detached for long runs). Unlike kermt-continue-pretrain, no starting checkpoint is loaded — the model is randomly initialized.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build custom AI prompts from scratch using guided workflows and patterns from a 2,500+ prompt database. Supports image, video, and text prompts for Midjourney, Flux, Leonardo AI, DALL-E, Sora, and 12 more models. Use when user says "build a prompt", "create a prompt", "write a prompt", "make me a prompt", "new prompt", or "prompt from scratch".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design finalization: generates production-quality Pretext-native HTML/CSS. Works with approved mockups from /design-shotgun, CEO plans from /plan-ceo-review, design review context from /plan-design-review, or from scratch with a user description. Text actually reflows, heights are computed, layouts are dynamic. 30KB overhead, zero deps. Smart API routing: picks the right Pretext patterns for each design type. Use when: "finalize this design", "turn this into HTML", "build me a page", "implement this design", or after any planning skill. Proactively suggest when user has approved a design or has a plan ready. (gstack) Voice triggers (speech-to-text aliases): "build the design", "code the mockup", "make it real".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Strip a problem to its irreducible fundamental truths and rebuild the solution from the ground up — free from analogy, convention, and inherited assumptions. Load when the user feels constrained by how something has always been done, when existing solutions feel expensive or inefficient for no good reason, when the user asks to think from first principles, challenge the fundamentals, or rebuild this from scratch. Also triggers on "why does it have to work this way", "what are the actual constraints here", "ignore what everyone else does", or when deep-thinking diagnoses a convention-break frame. Based on Aristotle's first principles method, popularised by Musk and Feynman. Produces genuinely novel solutions by eliminating convention.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.