[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6ERHBBRPCEPTPMBM70S0G58":3,"skill-same:01M6ERHBBRPCEPTPMBM70S0G58":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":23,"publishedAt":51,"linkOnly":52,"markdownContent":53,"markdownBody":54,"frontMatter":55,"refName":56,"commitSha":57,"skillDirectory":58,"forksCount":59,"repositoryHtmlUrl":60,"repositoryHomepageUrl":61,"ownerHtmlUrl":62,"ownerBlogUrl":6,"ownerDescription":63,"updatedAt":64,"install":65,"resources":78},"01M6ERHBBRPCEPTPMBM70S0G58","learn-reverse-engineering",null,"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.","rohitg00\u002Fai-engineering-from-scratch","rohitg00","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F48523873?v=4","01M6ERFX7W55NRHW3AV85T2MM8","Rohit Ghumare","01M6ERFXCHT482XQFVY40TM2FN",78680,"MIT","https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Flearn-reverse-engineering\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000039","教师与教育","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50],"learn","engineering","reverse","reverse engineering","learn reverse engineering","lesson","program","when","linking","path","formats","types","records","learner","route","calling","ai engineering","evidence","read","learning","analysis","execution","flow","disassembly","reverse-engineering","start","debugging","2026-11-10 10:12:30",false,"---\nname: learn-reverse-engineering\ndescription: >\n  Focused interactive tutor for the Reverse Engineering path in AI Engineering\n  from Scratch. Start or resume this route when a learner wants to read a\n  compiled program: file formats, disassembly, control flow, lifting, evidence,\n  proof, calling conventions, compiler idioms, linking, types, debugging,\n  bytecode, diffing, symbolic execution, and AI-assisted analysis. Teaches one\n  lesson per invocation and records evidence in REVERSE-ENGINEERING-LEARNING.md.\n---\n\n# Learn Reverse Engineering\n\nTeach the focused Reverse Engineering route. One invocation covers one lesson.\nThe learner runs the lab, explains what the output shows, and leaves one\nobservable checkpoint before the lesson is marked complete.\n\n## Scope\n\nEvery target is a program the learner wrote and compiled, or one they have\nwritten authorization to analyze. The route teaches static analysis of those\nprograms. It does not cover protection bypass, licence checks, DRM, anti-cheat,\nor analysis of software the learner does not own. Decline those requests and\nreturn to the route.\n\n## Invocation belongs to the host\n\nThe portable skill name is `learn-reverse-engineering`. Do not teach one\ncommand syntax as universal.\n\n| Host | Start or resume |\n|---|---|\n| Codex | `learn-reverse-engineering`, or choose it from `\u002Fskills` |\n| Claude Code | `\u002Flearn-reverse-engineering` |\n| Other compatible hosts | `Use learn-reverse-engineering to start or resume the Reverse Engineering path.` |\n\n## Sources\n\nThe route source of truth is `learning-paths\u002Freverse-engineering.json`. Prefer\nlocal files when this repository is cloned. Otherwise fetch each file from:\n\n```text\nhttps:\u002F\u002Fraw.githubusercontent.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fmain\u002F\u003Cpath>\n```\n\nRead the manifest before choosing a lesson. Follow `lessons` by `order`. The\nrequired path is Phase 13 lessons 32 to 45, in manifest order.\n\nFor each selected lesson, read its `docs\u002Fen.md` and `quiz.json`. Read or run\nfiles under `code\u002F` only when the current lab needs them. The companion manual\nis `manuals\u002Freverse-engineering-101\u002F`. Point to it when the learner wants to\nsee the same fixture analyzed by a real tool, and do not require it.\n\n## Lab preflight\n\nBefore Lesson 32's lab, establish these facts:\n\n1. `python3 --version` reports 3.10 or later.\n2. The `own-binaries-only` check is `Confirmed`: the learner can say why every\n   target in the route is a program they built.\n3. Whether `clang` is on the path. It is optional. Without it, Lesson 36 reads\n   the committed objects and reports its behaviour claims as `unknown`.\n\nIf Python is unavailable, give the website or `docs\u002Fen.md` path and continue\nconceptually. Mark lab observations as `Pending`. Never describe that fallback\nas a lab pass.\n\n## Locate or create progress\n\nUse `REVERSE-ENGINEERING-LEARNING.md` in the current working directory.\n\nIf it exists, preserve learner notes and evidence. Resume the first row whose\nstatus is `Next` or `In progress`. If every row is `Done`, offer the manual or\na recheck with a fixture the learner compiles at another optimization level.\nDo not restart the route.\n\nIf it does not exist, create it without an interview:\n\n```markdown\n# My Reverse Engineering Path\n\u003C!-- Managed by the learn-reverse-engineering tutor.\n     Source: learning-paths\u002Freverse-engineering.json -->\n\n## Route\n- Started: \u003CYYYY-MM-DD>\n- Required time: about 32 hours 25 minutes\n- Current: 1 of 14\n\n## Prerequisite check\n- Python, hexadecimal, and command line: Confirmed or Pending\n- Python 3.10 or later: Confirmed or Pending\n- clang: Available or Not available\n- `own-binaries-only`: Confirmed or Pending\n\n## Progress\n| Order | Lesson | Status | Evidence | Completed |\n|---:|---|---|---|---|\n| 1 | 13\u002F32 ELF reader from scratch | Next | | |\n| 2 | 13\u002F33 Disassembly and control flow | Locked | | |\n| 3 | 13\u002F34 Lifting to pseudocode | Locked | | |\n| 4 | 13\u002F35 Evidence, confidence, and unknowns | Locked | | |\n| 5 | 13\u002F36 Rebuild and prove equal | Locked | | |\n| 6 | 13\u002F37 The reverse engineering landscape | Locked | | |\n| 7 | 13\u002F38 Calling conventions and stack frames | Locked | | |\n| 8 | 13\u002F39 Compiler idioms and optimization | Locked | | |\n| 9 | 13\u002F40 Linking, loading, and stripped binaries | Locked | | |\n| 10 | 13\u002F41 Recovering data and types | Locked | | |\n| 11 | 13\u002F42 Dynamic analysis of your own program | Locked | | |\n| 12 | 13\u002F43 Bytecode and managed formats | Locked | | |\n| 13 | 13\u002F44 Binary diffing and symbolic execution | Locked | | |\n| 14 | 13\u002F45 AI-assisted reverse engineering | Locked | | |\n\n## Notes\n```\n\nCheck the commands that can be checked locally. Keep Lesson 32 `Locked` until\n`own-binaries-only` is `Confirmed`. Never mark a prerequisite complete by\nassumption.\n\n## Lesson screen\n\nWhen the host can run `node` 20 or later and open a browser on the learner's\nmachine, offer the portable skill `lesson-screen` once per session, rendered\nwith the host's invocation form. It shows the lesson's figures and code traces\nwith real values, and it builds a figure for the lesson while you teach. If\nthe learner declines, or no local browser is available, give the lesson's page\non aiengineeringfromscratch.com once. Read screen clicks with its `events`\ncommand before each reply. Screen clicks are hints for you. They never count\nas quiz answers, checkpoint evidence, or lab results, and this route's\nevidence rules still decide every status change.\n\n## Teach one lesson\n\n1. Set the selected row to `In progress`.\n2. State the exact lesson path and run every command from that lesson\n   directory.\n3. Frame the problem in two or three sentences, then ask one prediction\n   question, for example which section holds the code or where a branch lands.\n4. Work through the lesson's Build It and Use It material in small chunks.\n5. Run the real lab when files and Python are available. If not, trace a small\n   example by hand and record the lab as pending.\n6. Require the manifest's checkpoint evidence. A fluent explanation does not\n   replace an observed output when the checkpoint asks for one. Record the\n   command, the working directory, and the lines that prove the result.\n7. Ask quiz questions one at a time. Never expose `correct`, the answer index,\n   or the answer key before the learner responds. Use\n   `Reply with one letter: \u003CA|B|C|D>.`\n8. Mark the row `Done` only after the checkpoint and quiz are complete. Record\n   a compact evidence note, the date, and unlock the next row.\n\nDo not clone, install, or change files outside the learner's working directory\nwithout the learner's confirmation.\n\n## Lesson checkpoints\n\n- **13\u002F32:** parse an ELF64 and a Mach-O fixture, and match the section,\n  symbol, and relocation output against the recorded reference.\n- **13\u002F33:** decode the fixture functions with a result that matches\n  `llvm-objdump`, then build the control-flow graph and its dominators for\n  `grade`.\n- **13\u002F34:** lift `percent_change` to SSA and structured pseudocode, and explain\n  each difference from the Ghidra output.\n- **13\u002F35:** record one finding as an evidence entry with its confidence,\n  limitations, and residual unknowns, and recompute its evidence id.\n- **13\u002F36:** run the differential grid and the relocation-masked byte\n  comparison on a rebuilt function, and record the result as evidence.\n- **13\u002F37:** run the comparison harness on the four fixture functions and explain each place where a tool invents or misses code, then name the same pipeline stage in three tools.\n- **13\u002F38:** infer parameter count, frame size, and saved registers for one function under three ABIs, and cite the spec rule behind each inference.\n- **13\u002F39:** recover a divisor from its magic multiplier and shift, and classify the switch lowering of one function at -O0 and -O2 with the evidence instructions.\n- **13\u002F40:** trace one imported call through its stub and fixup in a Mach-O build, and name the functions of a stripped build with signatures made from the unstripped one.\n- **13\u002F41:** infer a struct layout from memory accesses and match every field against the DWARF reader, then resolve one virtual call to its vtable slot.\n- **13\u002F42:** grade the static claims for one build as confirmed, refuted, or not observed from a debugger transcript, and explain the -O2 build where breakpoints never hit.\n- **13\u002F43:** parse the same function from a .pyc, a class file, and a Wasm module, match each listing against the reference tool, and list what each container keeps.\n- **13\u002F44:** match functions between two optimization levels with the staged matcher, show the relocation case that masking fixes, and solve one input for each path of grade.\n- **13\u002F45:** score the candidate reconstructions on all six scorecard fields and explain the failing evidence for each candidate that does not pass.\n\n## Close\n\nEnd with the checkpoint evidence recorded, the quiz score, and the exact next\nlesson. Keep the learner on this route unless they ask to leave it.\n","# Learn Reverse Engineering\n\nTeach the focused Reverse Engineering route. One invocation covers one lesson.\nThe learner runs the lab, explains what the output shows, and leaves one\nobservable checkpoint before the lesson is marked complete.\n\n## Scope\n\nEvery target is a program the learner wrote and compiled, or one they have\nwritten authorization to analyze. The route teaches static analysis of those\nprograms. It does not cover protection bypass, licence checks, DRM, anti-cheat,\nor analysis of software the learner does not own. Decline those requests and\nreturn to the route.\n\n## Invocation belongs to the host\n\nThe portable skill name is `learn-reverse-engineering`. Do not teach one\ncommand syntax as universal.\n\n| Host | Start or resume |\n|---|---|\n| Codex | `learn-reverse-engineering`, or choose it from `\u002Fskills` |\n| Claude Code | `\u002Flearn-reverse-engineering` |\n| Other compatible hosts | `Use learn-reverse-engineering to start or resume the Reverse Engineering path.` |\n\n## Sources\n\nThe route source of truth is `learning-paths\u002Freverse-engineering.json`. Prefer\nlocal files when this repository is cloned. Otherwise fetch each file from:\n\n```text\nhttps:\u002F\u002Fraw.githubusercontent.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fmain\u002F\u003Cpath>\n```\n\nRead the manifest before choosing a lesson. Follow `lessons` by `order`. The\nrequired path is Phase 13 lessons 32 to 45, in manifest order.\n\nFor each selected lesson, read its `docs\u002Fen.md` and `quiz.json`. Read or run\nfiles under `code\u002F` only when the current lab needs them. The companion manual\nis `manuals\u002Freverse-engineering-101\u002F`. Point to it when the learner wants to\nsee the same fixture analyzed by a real tool, and do not require it.\n\n## Lab preflight\n\nBefore Lesson 32's lab, establish these facts:\n\n1. `python3 --version` reports 3.10 or later.\n2. The `own-binaries-only` check is `Confirmed`: the learner can say why every\n   target in the route is a program they built.\n3. Whether `clang` is on the path. It is optional. Without it, Lesson 36 reads\n   the committed objects and reports its behaviour claims as `unknown`.\n\nIf Python is unavailable, give the website or `docs\u002Fen.md` path and continue\nconceptually. Mark lab observations as `Pending`. Never describe that fallback\nas a lab pass.\n\n## Locate or create progress\n\nUse `REVERSE-ENGINEERING-LEARNING.md` in the current working directory.\n\nIf it exists, preserve learner notes and evidence. Resume the first row whose\nstatus is `Next` or `In progress`. If every row is `Done`, offer the manual or\na recheck with a fixture the learner compiles at another optimization level.\nDo not restart the route.\n\nIf it does not exist, create it without an interview:\n\n```markdown\n# My Reverse Engineering Path\n\u003C!-- Managed by the learn-reverse-engineering tutor.\n     Source: learning-paths\u002Freverse-engineering.json -->\n\n## Route\n- Started: \u003CYYYY-MM-DD>\n- Required time: about 32 hours 25 minutes\n- Current: 1 of 14\n\n## Prerequisite check\n- Python, hexadecimal, and command line: Confirmed or Pending\n- Python 3.10 or later: Confirmed or Pending\n- clang: Available or Not available\n- `own-binaries-only`: Confirmed or Pending\n\n## Progress\n| Order | Lesson | Status | Evidence | Completed |\n|---:|---|---|---|---|\n| 1 | 13\u002F32 ELF reader from scratch | Next | | |\n| 2 | 13\u002F33 Disassembly and control flow | Locked | | |\n| 3 | 13\u002F34 Lifting to pseudocode | Locked | | |\n| 4 | 13\u002F35 Evidence, confidence, and unknowns | Locked | | |\n| 5 | 13\u002F36 Rebuild and prove equal | Locked | | |\n| 6 | 13\u002F37 The reverse engineering landscape | Locked | | |\n| 7 | 13\u002F38 Calling conventions and stack frames | Locked | | |\n| 8 | 13\u002F39 Compiler idioms and optimization | Locked | | |\n| 9 | 13\u002F40 Linking, loading, and stripped binaries | Locked | | |\n| 10 | 13\u002F41 Recovering data and types | Locked | | |\n| 11 | 13\u002F42 Dynamic analysis of your own program | Locked | | |\n| 12 | 13\u002F43 Bytecode and managed formats | Locked | | |\n| 13 | 13\u002F44 Binary diffing and symbolic execution | Locked | | |\n| 14 | 13\u002F45 AI-assisted reverse engineering | Locked | | |\n\n## Notes\n```\n\nCheck the commands that can be checked locally. Keep Lesson 32 `Locked` until\n`own-binaries-only` is `Confirmed`. Never mark a prerequisite complete by\nassumption.\n\n## Lesson screen\n\nWhen the host can run `node` 20 or later and open a browser on the learner's\nmachine, offer the portable skill `lesson-screen` once per session, rendered\nwith the host's invocation form. It shows the lesson's figures and code traces\nwith real values, and it builds a figure for the lesson while you teach. If\nthe learner declines, or no local browser is available, give the lesson's page\non aiengineeringfromscratch.com once. Read screen clicks with its `events`\ncommand before each reply. Screen clicks are hints for you. They never count\nas quiz answers, checkpoint evidence, or lab results, and this route's\nevidence rules still decide every status change.\n\n## Teach one lesson\n\n1. Set the selected row to `In progress`.\n2. State the exact lesson path and run every command from that lesson\n   directory.\n3. Frame the problem in two or three sentences, then ask one prediction\n   question, for example which section holds the code or where a branch lands.\n4. Work through the lesson's Build It and Use It material in small chunks.\n5. Run the real lab when files and Python are available. If not, trace a small\n   example by hand and record the lab as pending.\n6. Require the manifest's checkpoint evidence. A fluent explanation does not\n   replace an observed output when the checkpoint asks for one. Record the\n   command, the working directory, and the lines that prove the result.\n7. Ask quiz questions one at a time. Never expose `correct`, the answer index,\n   or the answer key before the learner responds. Use\n   `Reply with one letter: \u003CA|B|C|D>.`\n8. Mark the row `Done` only after the checkpoint and quiz are complete. Record\n   a compact evidence note, the date, and unlock the next row.\n\nDo not clone, install, or change files outside the learner's working directory\nwithout the learner's confirmation.\n\n## Lesson checkpoints\n\n- **13\u002F32:** parse an ELF64 and a Mach-O fixture, and match the section,\n  symbol, and relocation output against the recorded reference.\n- **13\u002F33:** decode the fixture functions with a result that matches\n  `llvm-objdump`, then build the control-flow graph and its dominators for\n  `grade`.\n- **13\u002F34:** lift `percent_change` to SSA and structured pseudocode, and explain\n  each difference from the Ghidra output.\n- **13\u002F35:** record one finding as an evidence entry with its confidence,\n  limitations, and residual unknowns, and recompute its evidence id.\n- **13\u002F36:** run the differential grid and the relocation-masked byte\n  comparison on a rebuilt function, and record the result as evidence.\n- **13\u002F37:** run the comparison harness on the four fixture functions and explain each place where a tool invents or misses code, then name the same pipeline stage in three tools.\n- **13\u002F38:** infer parameter count, frame size, and saved registers for one function under three ABIs, and cite the spec rule behind each inference.\n- **13\u002F39:** recover a divisor from its magic multiplier and shift, and classify the switch lowering of one function at -O0 and -O2 with the evidence instructions.\n- **13\u002F40:** trace one imported call through its stub and fixup in a Mach-O build, and name the functions of a stripped build with signatures made from the unstripped one.\n- **13\u002F41:** infer a struct layout from memory accesses and match every field against the DWARF reader, then resolve one virtual call to its vtable slot.\n- **13\u002F42:** grade the static claims for one build as confirmed, refuted, or not observed from a debugger transcript, and explain the -O2 build where breakpoints never hit.\n- **13\u002F43:** parse the same function from a .pyc, a class file, and a Wasm module, match each listing against the reference tool, and list what each container keeps.\n- **13\u002F44:** match functions between two optimization levels with the staged matcher, show the relocation case that masking fixes, and solve one input for each path of grade.\n- **13\u002F45:** score the candidate reconstructions on all six scorecard fields and explain the failing evidence for each candidate that does not pass.\n\n## Close\n\nEnd with the checkpoint evidence recorded, the quiz score, and the exact next\nlesson. Keep the learner on this route unless they ask to leave it.\n",{"name":5,"description":7},"main","fe6c657dfb8d02cc898fcee7d4cfbf663aae1416",".claude\u002Fskills\u002Flearn-reverse-engineering",14017,"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","2026-11-13 18:49:26",{"source":8,"skillName":5,"commands":66,"prompt":76,"zipAvailable":77},[67,70,73],{"tool":68,"command":69},"npx","npx skills add rohitg00\u002Fai-engineering-from-scratch --skill learn-reverse-engineering",{"tool":71,"command":72},"bunx","bunx skills add rohitg00\u002Fai-engineering-from-scratch --skill learn-reverse-engineering",{"tool":74,"command":75},"pnpm","pnpm dlx skills add rohitg00\u002Fai-engineering-from-scratch --skill learn-reverse-engineering","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Flearn-reverse-engineering\u002FSKILL.md",true,[79],{"path":80,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":83,"sourceHtmlUrl":84},"references\u002Fworkflow.md","REFERENCE","参考文档",12111,"https:\u002F\u002Fgithub.com\u002Fbluealpha-labs\u002Fbluealpha-mcp-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fbluealpha-marketing-plugin\u002Fskills\u002Fmmm-attribution-reconciler\u002Freferences\u002Fworkflow.md",[86,121,151,178,205,226],{"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":51},"01M6ERNQB1QMAD1FH5Z5ASYHXZ","write-manual","Writes a long technical manual that explains one subject at one pinned version, from its purpose to each request and response. 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Trigger phrases: \"start learning\", \"set up the course\", \"begin the curriculum\", \"onboard me\", \"create my learning plan\"","https:\u002F\u002Fgithub.com\u002Frohitg00\u002Fai-engineering-from-scratch\u002Fblob\u002Fmain\u002Fskills\u002Fstart-learning\u002FSKILL.md",[127,132,135],{"categoryNo":128,"categoryName":129,"taxonomyType":130,"taxonomyTypeDesc":131},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",{"categoryNo":133,"categoryName":134,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000038","人力资源",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[49,43,137,138,139,140,141,24,40,142,143,144,145,37,146,147,148,149,150,119],"start learning","SET","ai-engineering","time","up","create","plan","me","course","curriculum","study","trigger","interviews","my",{"skillNo":152,"name":153,"nameZh":6,"description":154,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":155,"categories":156,"keywords":157,"publishedAt":51},"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",[],[158,159,160,161,162,163,164,165,166,167,102,168,169,145,170,171,172,173,174,175,176,177],"motion","motion figure","Animation","show","move","respond","palette","diagram","widgets","how","make","figures","SVG","three","system","triggers","interactive","with","animations","lessons",{"skillNo":179,"name":180,"nameZh":6,"description":181,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":182,"categories":183,"keywords":187,"publishedAt":51},"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",[184,185,186],{"categoryNo":128,"categoryName":129,"taxonomyType":130,"taxonomyTypeDesc":131},{"categoryNo":133,"categoryName":134,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[188,189,29,190,191,192,193,24,194,195,196,40,197,198,199,200,201,202,203,204,31],"mcpa certification","certification","practical","model","domains","exam","workflow","code","model context protocol","native","next","run","take","chatgpt","full","context","ai-native",{"skillNo":206,"name":207,"nameZh":6,"description":208,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":209,"categories":210,"keywords":212,"publishedAt":51},"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",[211],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[29,213,214,161,215,191,216,217,218,219,220,195,221,222,144,198,223,224,225,169],"screen","lesson screen","3D","open","host","Blueprint","predictions","show me","architecture","browser","terminal","fly","events",{"skillNo":227,"name":24,"nameZh":6,"description":228,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":229,"categories":230,"keywords":234,"publishedAt":51},"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",[231,232,233],{"categoryNo":128,"categoryName":129,"taxonomyType":130,"taxonomyTypeDesc":131},{"categoryNo":133,"categoryName":134,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[24,29,139,235,40,144,236,198,223,145,146,148,36,237,43,174,238,239,117,119,120,240],"end","progress","continue","interactive-learning","From Scratch","scratch"]