Undergraduate in Intelligent Science & Technology (Ningxia University). These repos are my working knowledge base: MIT/Stanford course material re-annotated bilingually (English source + 中文批注), plus the agent tooling I build to maintain it. Everything here is meant to be read by both humans and AI agents — each repo has an
llms.txtat its root.
| Repo | What is actually inside |
|---|---|
Introduction-to-Probability-6.041 |
MIT 6.041 Probability — bilingual lecture notes, recitation solutions, problem sets, midterm/final exams, textbook chunks, tutorials |
Introduction-to-Real-Analysis-18.100B |
MIT 18.100B Real Analysis — bilingual lecture notes, textbook translation, problem sets with solutions, exams, proof notes, subtitles |
Design-and-Analysis-of-Algorithms-6.046J |
MIT 6.046J Algorithms — bilingual lecture notes, recitation notes, problem sets with solutions, quizzes, final, review, code |
Convex-Optimization-EE364a |
Stanford EE364a Convex Optimization solutions & notes — 13 lecture decks, homework problem sets with official solutions, Boyd textbook + answer manual, extra exercises, EN/中文 |
Computer-Networking-CS144 |
Stanford CS144 Computer Networking labs & notes — Lab 0-6 handouts, weekly lecture notes, MOOC unit notes, midterm & final practice exams with answers, textbook, subtitles, EN/中文 |
Information-Theory |
MacKay ITILA Information Theory lecture notes & slides — 16 bilingual lecture notes, official l1-l16 MagicPoint slides, textbook PDF/EPUB with bilingual chapters, board snapshots, EN/中文 |
Mathematics-for-Computer-Science |
MIT 6.042J Mathematics for Computer Science — textbook PDF (920pp), chapter structure index, scanned Ch.18 random variables, TOC docx |
Computer-Systems-A-Programmer-s-Perspective |
CSAPP chapter & section index (Computer Systems: A Programmer's Perspective) — scanned TOC, Ch.2 info representation, Ch.8 exceptional control flow PDFs |
Introduction-to-Algorithms |
CLRS Introduction to Algorithms — bilingual EN/中文 book translation chunks (p005-242), MIT 6.006 lecture notes, problem set solutions, exams 1-14, subtitles. |
Introduction-to-Linear-Algebra |
Introduction to Linear Algebra (Strang, MIT 18.06) — scanned Chinese-edition PDF merged into 2 volumes by page order (p000-055, p056-105), with chapter/page index. |
Linear-Algebra-and-Learning-from-Data |
Linear Algebra and Learning from Data (Strang) — bilingual EN/中文 translations of chapters p001-250 and Parts IV-VII, 18.065 problem set solutions, lecture video transcripts. |
Introduction-to-Algorithms-codetry |
CLRS Introduction to Algorithms — code drills & practice: C/C++/Python exercise folders (loops, pointers, structs, BFS, Josephus, Yanghui), plus a few linear algebra notes. |
| Repo | What is actually inside |
|---|---|
dsh-reasonix-agent |
dsh-reasonix-agent — LLM agent harness config backup mirror + engineering notes, 2229 files: dsh presets & cordis.patch.yml, reasonix memory, agents/skills, PowerShell scripts, kb/ lessons |
Structured-Pseudocode-mind-language |
Structured-Pseudocode-mind-language — VS Code ext + bridge: .mind structured pseudocode semantic highlighting, LLM code-generation to Python 3 / C11, DeepSeek API, 35 files |
tool-box |
tool-box — Python scripts for PDF/TOC extraction, docx summary generation and image rendering; PowerShell ops (autocommit, doctor, backup); Windows .bat push |
diary |
diary — auto-generated daily journal notes in Markdown, 18 files: index.md plus days-public/YYYY-MM-DD.md dailies written by an LLM from dsh sessions, tool-call logs, window activity and Edge history |
desktop-tutorial |
desktop-tutorial — empty placeholder repo, created automatically by GitHub Desktop on first sign-in; 0 files, no README, nothing to search |
GitHub disallows /*/tree/ and /*/raw/ to GPTBot, ClaudeBot, PerplexityBot and friends,
so directory layouts are invisible to crawlers. Each repo therefore ships an llms.txt
(llmstxt.org format) stating what is really inside, with real paths.
- Docs via MCP:
https://gitmcp.io/TianQue6916/<repo>— GitMCP readsllms.txtfirst, thenREADME.md. - Repo search on GitHub indexes only name, description and topics — not README body. The one-line descriptions above are written to be the search surface; the READMEs carry the detail.
- Contents are personal study material. Textbooks and scans remain the copyright of their authors and publishers; buy the originals. Bilingual notes and translations are mine.
- Repository descriptions are deliberately keyword-dense: they are the only field GitHub search actually reads.