[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6ERNKG9FZ3WGJ87B975SHW5":3,"skill-same:01M6ERNKG9FZ3WGJ87B975SHW5":85},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":31,"publishedAt":52,"linkOnly":53,"markdownContent":54,"markdownBody":55,"frontMatter":56,"refName":62,"commitSha":63,"skillDirectory":64,"forksCount":65,"repositoryHtmlUrl":66,"repositoryHomepageUrl":67,"ownerHtmlUrl":68,"ownerBlogUrl":6,"ownerDescription":69,"updatedAt":70,"install":71,"resources":84},"01M6ERNKG9FZ3WGJ87B975SHW5","start-learning",null,"One-time onboarding for the AI Engineering from Scratch curriculum (542 lessons, 20 phases). Interviews the learner, runs the placement quiz, and writes LEARNING.md, a persistent study plan the learn skill drives. Trigger phrases: \"start learning\", \"set up the course\", \"begin the curriculum\", \"onboard me\", \"create my learning plan\"","rohitg00\u002Fai-engineering-from-scratch","rohitg00","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F48523873?v=4","01M6ERFX7W55NRHW3AV85T2MM8","Rohit Ghumare","01M6ERFXCHT482XQFVY40TM2FN",78488,"MIT","https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fblob\u002Fmain\u002Fskills\u002Fstart-learning\u002FSKILL.md",[18,23,28],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000038","人力资源","PROFESSION","适用职业",{"categoryNo":29,"categoryName":30,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000039","教师与教育",[32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51],"learning","start learning","start","for","my","interviews","trigger","study","curriculum","learner","course","me","plan","create","ai engineering","learn","up","time","ai-engineering","SET","2026-11-10 10:12:30",false,"---\nname: start-learning\nversion: 1.0.0\ndescription: >\n  One-time onboarding for the AI Engineering from Scratch curriculum (542\n  lessons, 20 phases). Interviews the learner, runs the placement quiz, and\n  writes LEARNING.md, a persistent study plan the learn skill drives.\n  Trigger phrases: \"start learning\", \"set up the course\", \"begin the\n  curriculum\", \"onboard me\", \"create my learning plan\"\ntags: [onboarding, curriculum, ai-engineering, learning-plan]\n---\n\n# Start Learning\n\nYou are onboarding a learner into the **AI Engineering from Scratch**\ncurriculum: 542 lessons across 20 phases, from linear algebra to autonomous\nagents. Your job is to produce `LEARNING.md`, a single file in the current\ndirectory that captures why they are learning, where they should start, and\nwhat their path looks like. Every later `learn` session reads and updates\nthis file, so treat it as the learner's source of truth.\n\nWorks with any agent. If your environment has a structured question\u002Foption\ntool, use it for every question; otherwise present lettered options as plain\ntext and wait for the reply.\n\n## Host invocation contract\n\nSkill names are portable, but invocation syntax belongs to the host. Before\nshowing a next command, use the correct form:\n\n- Codex: `start-learning`, `learn`, `course-guide`, and other `skill-name`\n  forms, or tell the learner to choose the skill from `\u002Fskills`.\n- Claude Code: `\u002Fstart-learning`, `\u002Flearn`, `\u002Fcourse-guide`, and other\n  `\u002Fskill-name` forms.\n- Other compatible hosts: natural language such as `Use learn to start my\n  first lesson.`\n\nNever present a Claude Code slash command as universal syntax. When the host is\nunknown, use the natural-language form.\n\n## Resume routing across course modes\n\nBefore generic onboarding, resolve every \"resume\" or \"continue\" request\nagainst these supported state files and their route owners:\n\n- `LEARNING.md` belongs to `learn` for the full curriculum.\n- `MCP-LEARNING.md` belongs to `learn-mcp` for the Model Context Protocol\n  (MCP) route.\n- `MCP-ENGINEERING-LEARNING.md` is the legacy filename for that same\n  `learn-mcp` route, not a separate route.\n- `AGENT-SKILLS-LEARNING.md` belongs to `learn-agent-skills`.\n- `REVERSE-ENGINEERING-LEARNING.md` belongs to `learn-reverse-engineering`.\n- `CLAUDE-CERTIFICATION.md` belongs to `claude-certification`.\n- `INTERVIEW-LEARNING.md` belongs to `interview-prep` for interview practice.\n\nIf the learner names a route in a resume or continue request, dispatch to its\nowner immediately even when other state files exist, then stop this skill.\n\nFor an unnamed resume or continue request, collect the owners whose state files\nexist, grouping both MCP filenames under `learn-mcp`. If exactly one route owner\nremains, invoke it and stop this skill before generic onboarding. `learn-mcp`\nowns legacy-file migration and collision reporting. If two or more route owners\nremain, list their learner-facing route names and ask which route to resume\nbefore running placement or changing any state. If none exist, continue with\ngeneric onboarding. Never infer a route from file recency or merge one route's\nprogress into another state file.\n\nLegacy runtimes may expose `learn-mcp-engineering` as an alias. Accept it only\nto reach `learn-mcp`; render every learner-facing handoff as `learn-mcp` and\nname the route Model Context Protocol (MCP).\n\n## Focused MCP handoff\n\nIf the learner explicitly wants Model Context Protocol (MCP) rather than the\nfull course, do not run placement and do not create `LEARNING.md`. Route to\nthe portable skill `learn-mcp`, whose source is\n`learning-paths\u002Fmodel-context-protocol.json` and whose state file is\n`MCP-LEARNING.md`. Use `learn-mcp` in Codex,\n`\u002Flearn-mcp` in Claude Code, or ask another compatible host to use\n`learn-mcp`. The dedicated tutor owns lesson selection, wire\nevidence, and the public-deployment security gate.\n\n## Focused Agent Skills handoff\n\nIf the learner explicitly wants Agent Skills instead of the full course, or\n`AGENT-SKILLS-LEARNING.md` exists and they ask to resume that route, do not run\nplacement and do not create `LEARNING.md`. Route to the portable skill\n`learn-agent-skills`, whose source is `learning-paths\u002Fagent-skills.json` and\nwhose state file is `AGENT-SKILLS-LEARNING.md`. Use `learn-agent-skills` in\nCodex, `\u002Flearn-agent-skills` in Claude Code, or ask another compatible host to\nuse `learn-agent-skills`. The dedicated tutor owns the five-lesson order,\nreal-host evidence, sandbox boundaries, the Lesson 25 and tool-poisoning\nprerequisite gate before Lesson 26, and the release gate.\n\n## Focused Reverse Engineering handoff\n\nIf the learner explicitly wants Reverse Engineering instead of the full course,\nor `REVERSE-ENGINEERING-LEARNING.md` exists and they ask to resume that route,\ndo not run placement and do not create `LEARNING.md`. Route to the portable\nskill `learn-reverse-engineering`, whose source is\n`learning-paths\u002Freverse-engineering.json` and whose state file is\n`REVERSE-ENGINEERING-LEARNING.md`. Use `learn-reverse-engineering` in Codex,\n`\u002Flearn-reverse-engineering` in Claude Code, or ask another compatible host to\nuse `learn-reverse-engineering`.\n\nIf `LEARNING.md` already exists, do not overwrite it. Summarize what it says\n(mission, entry point, progress so far) and offer exactly three paths:\n\n- **Resume**: invoke `learn` with the host syntax above; skip the interview and\n  placement entirely.\n- **Re-run placement**: administer the quiz again, then update only the\n  Placement section and the Path statuses; keep the Mission, the Progress\n  log, and the Review queue untouched.\n- **Start over**: only after an explicit confirmation, rename the current\n  file to `LEARNING-\u003CYYYY-MM-DD>.md` as an archive, then proceed with the\n  full onboarding below. Never delete or overwrite their history silently.\n\n## Step 1: The interview (3 questions, keep it short)\n\n1. **Why are you learning AI engineering?** Free text. Examples to offer:\n   ship an AI product, career change, understand what I already use daily,\n   research. Capture their answer in their own words because it grounds every\n   future lesson explanation.\n2. **How much time per week?** Options: ~2 h, ~5 h, ~10 h, \"as fast as\n   possible\". Used only to phrase the pace honestly, never to cut content.\n3. **What do you most want to build by the end?** One line. An agent, a\n   trained model, a RAG product, \"not sure yet\" is fine.\n\nDo not ask more than these three. The placement quiz measures knowledge;\nthe interview only captures intent.\n\n## Step 2: Placement\n\nRun the placement quiz from the `find-your-level` skill (it installs\nalongside this one): 5 areas, 10 questions, mapped to an entry phase. Preserve\nthat skill's answer-isolation contract: do not preload later answer-key rounds\nor replace neutral `\u003Cletter>` placeholders with real option letters.\n\nIf the learner says they already know where they want to start (\"just start\nme at phase 7\"), respect that and skip the quiz, with the same output\ncontract as a quiz run so the `learn` tutor always finds a well-formed plan:\n\n- Validate the phase is 0-19 and resolve its canonical name; if it does not\n  resolve, list the 20 phases and ask them to pick.\n- In the Path table: phases below the entry point are `Skip`, the entry\n  point and everything above are `Do` (no `Review` rows because there are no area\n  scores to infer them from), and the Est. hours total is the sum of the\n  `Do` rows.\n- In the Placement section write `Score: self-selected` instead of a\n  number.\n\n## Step 3: Write LEARNING.md\n\nCreate `LEARNING.md` in the current directory with exactly these sections:\n\n```markdown\n# My AI Engineering Path\n\u003C!-- Managed by the ai-engineering-from-scratch learning skills.\n     Repo: https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch -->\n\n## Mission\n\u003Ctheir answer to question 1, in their words, plus the build goal from question 3>\n\n## Placement\n- Date: \u003CYYYY-MM-DD>\n- Score: \u003Ctotal>\u002F10 with the area breakdown, or exactly `self-selected` when the quiz was skipped\n- Entry point: Phase \u003CN>: \u003Cname>\n- Pace: ~\u003Chours>\u002Fweek\n\n## Path\n| Phase | Name | Status | Est. hours |\n|-------|------|--------|------------|\n\u003Call 20 phases; Status is Skip, Review, Do, or Done from the placement\nresult. Hours come from ROADMAP.md: read it locally if the repo is cloned,\notherwise fetch\nhttps:\u002F\u002Fraw.githubusercontent.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fmain\u002FROADMAP.md>\n\n## Progress log\n| Date | Lesson | Quiz | Note |\n|------|--------|------|------|\n\n## Review queue\n\u003Cempty for now; learn adds lessons the quizzes flag>\n```\n\n## Step 4: Hand off\n\nClose with three lines, nothing more:\n\n- Their entry point and total estimated hours for the Review + Do phases.\n- Give the host-correct invocation for `learn` and say that it starts the first\n  lesson and picks up from this file every time.\n- Give the host-correct invocation for `course-guide \u003Ctopic>` and say that it\n  can jump to a specific topic instead.\n","# Start Learning\n\nYou are onboarding a learner into the **AI Engineering from Scratch**\ncurriculum: 542 lessons across 20 phases, from linear algebra to autonomous\nagents. Your job is to produce `LEARNING.md`, a single file in the current\ndirectory that captures why they are learning, where they should start, and\nwhat their path looks like. Every later `learn` session reads and updates\nthis file, so treat it as the learner's source of truth.\n\nWorks with any agent. If your environment has a structured question\u002Foption\ntool, use it for every question; otherwise present lettered options as plain\ntext and wait for the reply.\n\n## Host invocation contract\n\nSkill names are portable, but invocation syntax belongs to the host. Before\nshowing a next command, use the correct form:\n\n- Codex: `start-learning`, `learn`, `course-guide`, and other `skill-name`\n  forms, or tell the learner to choose the skill from `\u002Fskills`.\n- Claude Code: `\u002Fstart-learning`, `\u002Flearn`, `\u002Fcourse-guide`, and other\n  `\u002Fskill-name` forms.\n- Other compatible hosts: natural language such as `Use learn to start my\n  first lesson.`\n\nNever present a Claude Code slash command as universal syntax. When the host is\nunknown, use the natural-language form.\n\n## Resume routing across course modes\n\nBefore generic onboarding, resolve every \"resume\" or \"continue\" request\nagainst these supported state files and their route owners:\n\n- `LEARNING.md` belongs to `learn` for the full curriculum.\n- `MCP-LEARNING.md` belongs to `learn-mcp` for the Model Context Protocol\n  (MCP) route.\n- `MCP-ENGINEERING-LEARNING.md` is the legacy filename for that same\n  `learn-mcp` route, not a separate route.\n- `AGENT-SKILLS-LEARNING.md` belongs to `learn-agent-skills`.\n- `REVERSE-ENGINEERING-LEARNING.md` belongs to `learn-reverse-engineering`.\n- `CLAUDE-CERTIFICATION.md` belongs to `claude-certification`.\n- `INTERVIEW-LEARNING.md` belongs to `interview-prep` for interview practice.\n\nIf the learner names a route in a resume or continue request, dispatch to its\nowner immediately even when other state files exist, then stop this skill.\n\nFor an unnamed resume or continue request, collect the owners whose state files\nexist, grouping both MCP filenames under `learn-mcp`. If exactly one route owner\nremains, invoke it and stop this skill before generic onboarding. `learn-mcp`\nowns legacy-file migration and collision reporting. If two or more route owners\nremain, list their learner-facing route names and ask which route to resume\nbefore running placement or changing any state. If none exist, continue with\ngeneric onboarding. Never infer a route from file recency or merge one route's\nprogress into another state file.\n\nLegacy runtimes may expose `learn-mcp-engineering` as an alias. Accept it only\nto reach `learn-mcp`; render every learner-facing handoff as `learn-mcp` and\nname the route Model Context Protocol (MCP).\n\n## Focused MCP handoff\n\nIf the learner explicitly wants Model Context Protocol (MCP) rather than the\nfull course, do not run placement and do not create `LEARNING.md`. Route to\nthe portable skill `learn-mcp`, whose source is\n`learning-paths\u002Fmodel-context-protocol.json` and whose state file is\n`MCP-LEARNING.md`. Use `learn-mcp` in Codex,\n`\u002Flearn-mcp` in Claude Code, or ask another compatible host to use\n`learn-mcp`. The dedicated tutor owns lesson selection, wire\nevidence, and the public-deployment security gate.\n\n## Focused Agent Skills handoff\n\nIf the learner explicitly wants Agent Skills instead of the full course, or\n`AGENT-SKILLS-LEARNING.md` exists and they ask to resume that route, do not run\nplacement and do not create `LEARNING.md`. Route to the portable skill\n`learn-agent-skills`, whose source is `learning-paths\u002Fagent-skills.json` and\nwhose state file is `AGENT-SKILLS-LEARNING.md`. Use `learn-agent-skills` in\nCodex, `\u002Flearn-agent-skills` in Claude Code, or ask another compatible host to\nuse `learn-agent-skills`. The dedicated tutor owns the five-lesson order,\nreal-host evidence, sandbox boundaries, the Lesson 25 and tool-poisoning\nprerequisite gate before Lesson 26, and the release gate.\n\n## Focused Reverse Engineering handoff\n\nIf the learner explicitly wants Reverse Engineering instead of the full course,\nor `REVERSE-ENGINEERING-LEARNING.md` exists and they ask to resume that route,\ndo not run placement and do not create `LEARNING.md`. Route to the portable\nskill `learn-reverse-engineering`, whose source is\n`learning-paths\u002Freverse-engineering.json` and whose state file is\n`REVERSE-ENGINEERING-LEARNING.md`. Use `learn-reverse-engineering` in Codex,\n`\u002Flearn-reverse-engineering` in Claude Code, or ask another compatible host to\nuse `learn-reverse-engineering`.\n\nIf `LEARNING.md` already exists, do not overwrite it. Summarize what it says\n(mission, entry point, progress so far) and offer exactly three paths:\n\n- **Resume**: invoke `learn` with the host syntax above; skip the interview and\n  placement entirely.\n- **Re-run placement**: administer the quiz again, then update only the\n  Placement section and the Path statuses; keep the Mission, the Progress\n  log, and the Review queue untouched.\n- **Start over**: only after an explicit confirmation, rename the current\n  file to `LEARNING-\u003CYYYY-MM-DD>.md` as an archive, then proceed with the\n  full onboarding below. Never delete or overwrite their history silently.\n\n## Step 1: The interview (3 questions, keep it short)\n\n1. **Why are you learning AI engineering?** Free text. Examples to offer:\n   ship an AI product, career change, understand what I already use daily,\n   research. Capture their answer in their own words because it grounds every\n   future lesson explanation.\n2. **How much time per week?** Options: ~2 h, ~5 h, ~10 h, \"as fast as\n   possible\". Used only to phrase the pace honestly, never to cut content.\n3. **What do you most want to build by the end?** One line. An agent, a\n   trained model, a RAG product, \"not sure yet\" is fine.\n\nDo not ask more than these three. The placement quiz measures knowledge;\nthe interview only captures intent.\n\n## Step 2: Placement\n\nRun the placement quiz from the `find-your-level` skill (it installs\nalongside this one): 5 areas, 10 questions, mapped to an entry phase. Preserve\nthat skill's answer-isolation contract: do not preload later answer-key rounds\nor replace neutral `\u003Cletter>` placeholders with real option letters.\n\nIf the learner says they already know where they want to start (\"just start\nme at phase 7\"), respect that and skip the quiz, with the same output\ncontract as a quiz run so the `learn` tutor always finds a well-formed plan:\n\n- Validate the phase is 0-19 and resolve its canonical name; if it does not\n  resolve, list the 20 phases and ask them to pick.\n- In the Path table: phases below the entry point are `Skip`, the entry\n  point and everything above are `Do` (no `Review` rows because there are no area\n  scores to infer them from), and the Est. hours total is the sum of the\n  `Do` rows.\n- In the Placement section write `Score: self-selected` instead of a\n  number.\n\n## Step 3: Write LEARNING.md\n\nCreate `LEARNING.md` in the current directory with exactly these sections:\n\n```markdown\n# My AI Engineering Path\n\u003C!-- Managed by the ai-engineering-from-scratch learning skills.\n     Repo: https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch -->\n\n## Mission\n\u003Ctheir answer to question 1, in their words, plus the build goal from question 3>\n\n## Placement\n- Date: \u003CYYYY-MM-DD>\n- Score: \u003Ctotal>\u002F10 with the area breakdown, or exactly `self-selected` when the quiz was skipped\n- Entry point: Phase \u003CN>: \u003Cname>\n- Pace: ~\u003Chours>\u002Fweek\n\n## Path\n| Phase | Name | Status | Est. hours |\n|-------|------|--------|------------|\n\u003Call 20 phases; Status is Skip, Review, Do, or Done from the placement\nresult. Hours come from ROADMAP.md: read it locally if the repo is cloned,\notherwise fetch\nhttps:\u002F\u002Fraw.githubusercontent.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fmain\u002FROADMAP.md>\n\n## Progress log\n| Date | Lesson | Quiz | Note |\n|------|--------|------|------|\n\n## Review queue\n\u003Cempty for now; learn adds lessons the quizzes flag>\n```\n\n## Step 4: Hand off\n\nClose with three lines, nothing more:\n\n- Their entry point and total estimated hours for the Review + Do phases.\n- Give the host-correct invocation for `learn` and say that it starts the first\n  lesson and picks up from this file every time.\n- Give the host-correct invocation for `course-guide \u003Ctopic>` and say that it\n  can jump to a specific topic instead.\n",{"name":5,"tags":57,"version":60,"description":61},[58,40,50,59],"onboarding","learning-plan","1.0.0","One-time onboarding for the AI Engineering from Scratch curriculum (542 lessons, 20 phases). Interviews the learner, runs the placement quiz, and writes LEARNING.md, a persistent study plan the learn skill drives. Trigger phrases: \"start learning\", \"set up the course\", \"begin the curriculum\", \"onboard me\", \"create my learning plan\"\n","main","ddaad269bc5ae3c9c1e73251e0500b9fabd9181b","skills\u002Fstart-learning",13971,"https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch","https:\u002F\u002Faiengineeringfromscratch.com","https:\u002F\u002Fgithub.com\u002Frohitg00","Engineer | DevRel | GDE | CNCF, AAIF, Claude, Devin, PE Ambassador | Docker Captain | AWS CB | Ex - iii, Cloudera, Solo.io, Cerbos, Oracle, Reliance Jio","2026-11-11 20:45:16",{"source":8,"skillName":5,"commands":72,"prompt":82,"zipAvailable":83},[73,76,79],{"tool":74,"command":75},"npx","npx skills add rohitg00\u002Fai-engineering-from-scratch --skill start-learning",{"tool":77,"command":78},"bunx","bunx skills add rohitg00\u002Fai-engineering-from-scratch --skill start-learning",{"tool":80,"command":81},"pnpm","pnpm dlx skills add rohitg00\u002Fai-engineering-from-scratch --skill start-learning","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fblob\u002Fmain\u002Fskills\u002Fstart-learning\u002FSKILL.md",true,[],[86,120,147,176,197,213],{"skillNo":87,"name":88,"nameZh":6,"description":89,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":90,"categories":91,"keywords":92,"publishedAt":52},"01M6ERNQB1QMAD1FH5Z5ASYHXZ","write-manual","Writes a long technical manual that explains one subject at one pinned version, from its purpose to each request and response. Every listing comes from an offline capture, every claim traces to a ranked source, and an audit must report TOTAL 0. Use it for \"write a manual\", \"write a 101 manual for \u003Csubject>\", \"manual.json\", \"add a manual section\", \"build a capture kit\", \"audit the manual\", or \"pin a spec version and document it\".","https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fblob\u002Fmain\u002Fskills\u002Fwrite-manual\u002FSKILL.md",[],[93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,35,119],"write","write manual","manual","technical-writing","claim","writing","documentation","audit","offline","add","long","technical","use","document","pin","version","build","manuals","specifications","json","report","kit","listing","request","at","source","section",{"skillNo":121,"name":122,"nameZh":6,"description":123,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":124,"categories":125,"keywords":126,"publishedAt":52},"01M6ERNECV0WVSTXHX8KRF9MBJ","motion-figure","Builds figures that move or respond to the reader, in three tiers: SMIL animations and slider widgets inside lessons, interactive mechanism figures that show the named parts of a real system with a computed verdict, and ordered dither bands in the course palette. Triggers: \"animated figure\", \"add a slider widget\", \"interactive figure\", \"show how this system works\", \"make this diagram move\", \"dither masthead\", \"mechanism figure\", \"figure fence\".","https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fblob\u002Fmain\u002Fskills\u002Fmotion-figure\u002FSKILL.md",[],[127,128,129,130,131,132,133,134,135,136,102,137,138,42,139,140,141,142,143,144,145,146],"motion","motion figure","Animation","show","move","respond","palette","diagram","widgets","how","make","figures","SVG","three","system","triggers","interactive","with","animations","lessons",{"skillNo":148,"name":149,"nameZh":6,"description":150,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":151,"categories":152,"keywords":156,"publishedAt":52},"01M6ERNAC0DQ8ER3A99VQBXNNZ","mcpa-certification","AI-native tutor and onboarding workflow for the MCPA (Model Context Protocol Associate) certification in AI Engineering from Scratch. Use when a learner wants to prepare for the MCPA, resume their certification path, learn the next lesson interactively, run and verify practical labs, take the diagnostic or a full mock, or remediate weak exam domains from GitHub with Claude Code, Codex, ChatGPT, Cursor, or another agent.","https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fblob\u002Fmain\u002Fskills\u002Fmcpa-certification\u002FSKILL.md",[153,154,155],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},{"categoryNo":29,"categoryName":30,"taxonomyType":26,"taxonomyTypeDesc":27},[157,158,159,160,161,162,163,47,164,165,166,46,167,168,169,170,171,172,173,174,175],"mcpa certification","certification","lesson","practical","model","domains","exam","workflow","code","model context protocol","native","next","run","take","chatgpt","full","context","ai-native","when",{"skillNo":177,"name":178,"nameZh":6,"description":179,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":180,"categories":181,"keywords":183,"publishedAt":52},"01M6ERN5TAAAJ7FE9N86SX6M2M","lesson-screen","Opens a lesson screen in the browser next to the terminal while a course tutor teaches. It shows the lesson's registered figures, code traces with real values, and clickable predictions. It also builds a figure for the lesson on the fly with the course figure skills and any figure skill the host has installed: a blueprint, a mechanism, an isometric machine, or a 3D model. Clicks return to the tutor as events. Trigger phrases: \"open the lesson screen\", \"show me this visually\", \"show this in 3D\", \"draw the architecture\", \"visualize this lesson\", \"build a figure for this lesson\", \"lesson screen\".","https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fblob\u002Fmain\u002Fskills\u002Flesson-screen\u002FSKILL.md",[182],{"categoryNo":29,"categoryName":30,"taxonomyType":26,"taxonomyTypeDesc":27},[159,184,185,130,186,161,187,188,189,190,191,165,192,193,43,168,194,195,196,138],"screen","lesson screen","3D","open","host","Blueprint","predictions","show me","architecture","browser","terminal","fly","events",{"skillNo":198,"name":47,"nameZh":6,"description":199,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":200,"categories":201,"keywords":205,"publishedAt":52},"01M6ERN1HS8HW1TRJVX5P7SPY0","Interactive lesson tutor for the AI Engineering from Scratch curriculum. Reads LEARNING.md, fetches the next lesson, teaches it section by section in the terminal, quizzes at the end, and records progress. Works cloned or entirely over raw.githubusercontent.com — no setup required. Trigger phrases: \"next lesson\", \"teach me\", \"continue the course\", \"let's learn\", \"resume learning\"","https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fblob\u002Fmain\u002Fskills\u002Flearn\u002FSKILL.md",[202,203,204],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},{"categoryNo":29,"categoryName":30,"taxonomyType":26,"taxonomyTypeDesc":27},[47,159,50,206,46,43,207,168,194,42,40,38,208,209,32,143,210,211,117,35,119,212],"end","progress","records","continue","interactive-learning","From Scratch","scratch",{"skillNo":214,"name":215,"nameZh":6,"description":216,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":217,"categories":218,"keywords":220,"publishedAt":52},"01M6ERMX6FFWGB9NPDN8FV4QYG","learn-reverse-engineering","Focused interactive tutor for the Reverse Engineering path in AI Engineering from Scratch. Start or resume this route when a learner wants to read a compiled program: file formats, disassembly, control flow, lifting, evidence, proof, calling conventions, compiler idioms, linking, types, debugging, bytecode, diffing, symbolic execution, and AI-assisted analysis. Teaches one lesson per invocation and records evidence in REVERSE-ENGINEERING-LEARNING.md.","https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fblob\u002Fmain\u002Fskills\u002Flearn-reverse-engineering\u002FSKILL.md",[219],{"categoryNo":29,"categoryName":30,"taxonomyType":26,"taxonomyTypeDesc":27},[47,221,222,223,224,159,225,226,227,228,46,229,230,231,34,232,233,41,208,32,234,235,175,236,237,238,239],"learn reverse engineering","engineering","reverse","reverse engineering","types","reverse-engineering","debugging","analysis","route","read","flow","disassembly","evidence","execution","calling","program","linking","formats","path"]