skill
interview-cheatsheet
Generate a long-form Chinese interview-prep cheat sheet on a specific ML/LLM topic — formulas with derivations, from-scratch PyTorch code, comparison tables, and 25 高频面试题 (L1 必会 / L2 进阶 / L3 顶级 lab). Use when the user says '写面试 cheat sheet', '写一份 X 教程', '帮我准备 Y 面试题', '出一份 X 速查', or wants a 600-1000 line Chinese tutorial on a specific ML topic.
Description as published by the maintainer. Source
- active
active — Most recent push to the repository was 2026-08-05.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 14,334 | Stars on the repository that contains this skill, not on the skill itself. A collection of fifty skills shares one number, so it says nothing about this particular skill. | cumulative, all time | GitHub | |
| Last commit | 2026-08-05 | Most recent push to the containing repository. It may reflect work on a different skill in the same collection. | point in time | GitHub | |
| repository status | active | The repository holding this skill exists and is not archived. | as of fetch | GitHub |
Will this work with your setup?
Install location suggests this is meant for claude-code. The author tagged this repository "claude-code-skills" on GitHub. That is their statement of intent, not a test result.
We have not run this skill against a task with and without it enabled, so we cannot tell you whether it improves anything, what it costs in tokens, or whether it duplicates behaviour your harness already has. When we have run that test, the result will appear on this page with the task, the versions and the budget it used.
The skill definition lives at skills/interview-cheatsheet/SKILL.md in https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.
Where to get it
Also from wanshuiyin
-
wanshuiyin-auto-claude-code-research-in-sleep-ablation-planner
— last commit 2026-08-05
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper s…
-
wanshuiyin-auto-claude-code-research-in-sleep-alphaxiv
— last commit 2026-08-05
Quick single-paper lookup via AlphaXiv LLM-optimized summaries with tiered source fallback. Use when user says "explain…
-
wanshuiyin-auto-claude-code-research-in-sleep-analyze-results
— last commit 2026-08-05
Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze…
-
wanshuiyin-auto-claude-code-research-in-sleep-arxiv
— last commit 2026-08-05
Search, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch…
-
wanshuiyin-auto-claude-code-research-in-sleep-auto-paper-improvement-loop
— last commit 2026-08-05
Autonomously improve a generated paper via GPT-5.6-Sol xhigh review → implement fixes → recompile, for 2 rounds. Use wh…
-
wanshuiyin-auto-claude-code-research-in-sleep-auto-review-loop
— last commit 2026-08-05
Autonomous multi-round research review loop. Repeatedly reviews via external reviewer backend (Codex or manual), implem…
-
wanshuiyin-auto-claude-code-research-in-sleep-auto-review-loop-llm
— last commit 2026-08-05
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment v…
-
wanshuiyin-auto-claude-code-research-in-sleep-auto-review-loop-minimax
— last commit 2026-08-05
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP fo…
-
wanshuiyin-auto-claude-code-research-in-sleep-citation-audit
— last commit 2026-08-05
Zero-context verification that every bibliographic entry in the paper is real, correctly attributed, and used in a cont…
-
wanshuiyin-auto-claude-code-research-in-sleep-claims-drafting
— last commit 2026-08-05
Draft patent claims for an invention. Use when user says \"撰写权利要求\", \"draft claims\", \"写权利要求书\", \"claim drafting\",…
Bring your own setup
We take apart real AI setups every week and show what broke, what cost too much, and what the trace actually said. If you run agents on real work, that is where the useful conversation is.
Join ZBS AI Practice Lab