DeepTutor CLI
HKUDS/DeepTutor
Teaches the agent to set up and run DeepTutor from the command line: chat and capabilities, knowledge bases, partners, memory, sessions, notebooks and the server or Web app.
cheat-on-skill 的核心。连 BOSS 直聘真实招聘数据 + 网页信号，按用户能力画像找「高薪 × 你学得动 × AI 增强」交集里的候选岗位。每个岗位给：薪资量级 / 需求热度 / 你的差距 / 可学性分 / 诚实学习周期，并过 AI 影响分类与反诈红线。触发词："帮我找岗位"/"找AI时代高薪工作"/"有什么我能学的高薪岗"/"skill scan"/"扫一遍招聘"。前置：需要…
Install Skill Scan
$ npx skills add XBuilderLAB/cheat-on-skill --skill skill-scan -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install XBuilderLAB/cheat-on-skill skill-scan --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/XBuilderLAB/cheat-on-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/skill-scan .claude/skills/skill-scan && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "skill-scan" agent skill from https://github.com/XBuilderLAB/cheat-on-skill/tree/main/skills/skill-scan into .claude/skills/skill-scan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-scan", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/XBuilderLAB/cheat-on-skill/tree/main/skills/skill-scanType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add XBuilderLAB/cheat-on-skill --skill skill-scan -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install XBuilderLAB/cheat-on-skill skill-scan --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/XBuilderLAB/cheat-on-skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/skill-scan .agents/skills/skill-scan && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "skill-scan" agent skill from https://github.com/XBuilderLAB/cheat-on-skill/tree/main/skills/skill-scan into .agents/skills/skill-scan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-scan", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add XBuilderLAB/cheat-on-skill --skill skill-scan -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install XBuilderLAB/cheat-on-skill skill-scan --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/XBuilderLAB/cheat-on-skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/skill-scan .cursor/skills/skill-scan && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "skill-scan" agent skill from https://github.com/XBuilderLAB/cheat-on-skill/tree/main/skills/skill-scan into .cursor/skills/skill-scan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-scan", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/XBuilderLAB/cheat-on-skill.git --path skills/skill-scan--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add XBuilderLAB/cheat-on-skill --skill skill-scan -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install XBuilderLAB/cheat-on-skill skill-scan --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/XBuilderLAB/cheat-on-skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/skill-scan .gemini/skills/skill-scan && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "skill-scan" agent skill from https://github.com/XBuilderLAB/cheat-on-skill/tree/main/skills/skill-scan into .gemini/skills/skill-scan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-scan", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install XBuilderLAB/cheat-on-skill skill-scanInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add XBuilderLAB/cheat-on-skill --skill skill-scan -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/XBuilderLAB/cheat-on-skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/skill-scan .github/skills/skill-scan && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "skill-scan" agent skill from https://github.com/XBuilderLAB/cheat-on-skill/tree/main/skills/skill-scan into .github/skills/skill-scan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-scan", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add XBuilderLAB/cheat-on-skill --skill skill-scan -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install XBuilderLAB/cheat-on-skill skill-scan --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/XBuilderLAB/cheat-on-skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/skill-scan .opencode/skills/skill-scan && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "skill-scan" agent skill from https://github.com/XBuilderLAB/cheat-on-skill/tree/main/skills/skill-scan into .opencode/skills/skill-scan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-scan", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
skill-scan- GitHub stars
- 194
- Used in
- 1 other repo
- Token cost
- ~1.2k tokens
- SKILL.md length
- 313 words
- Files
- 1
- Skills in repo
- 4
- Repo updated
- First seen
- Licence
- MIT
At a glance
cheat-on-skill 的核心。连 BOSS 直聘真实招聘数据 + 网页信号，按用户能力画像找「高薪 × 你学得动 × AI 增强」交集里的候选岗位。每个岗位给：薪资量级 / 需求热度 / 你的差距 / 可学性分 / 诚实学习周期，并过 AI 影响分类与反诈红线。触发词："帮我找岗位"/"找AI时代高薪工作"/"有什么我能学的高薪岗"/"skill scan"/"扫一遍招聘"。前置：需要…
- Works in 9 steps: 读上下文 → 按档位锁定搜索词 → 取真实招聘数据（BOSS adapter，human-in-the-loop） → …
- Education work in your project
- SKILL.md covers 核心方法（先读这条）, 铁律 and 流程
- Calls node; reaches zhipin.com
What it does
Skill Scan is an agent skill from XBuilderLAB/cheat-on-skill. cheat-on-skill 的核心。连 BOSS 直聘真实招聘数据 + 网页信号，按用户能力画像找「高薪 × 你学得动 × AI 增强」交集里的候选岗位。每个岗位给：薪资量级 / 需求热度 / 你的差距 / 可学性分 / 诚实学习周期，并过 AI 影响分类与反诈红线。触发词："帮我找岗位"/"找AI时代高薪工作"/"有什么我能学的高薪岗"/"skill scan"/"扫一遍招聘"。前置：需要 .skill-state.json（无则先路由到 skill-init）。
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Education. The repository describes itself as: 帮你在 AI 时代找到一份高薪 × 你学得动 × 不会被 AI 吃掉的工作，并给出个性化学习陪跑计划。能力匹配 + 可学性闸门 + BOSS 直聘真实招聘数据 + 反诈。 The licence is MIT.
When your agent uses it
- Education work in your project
Example prompts
- “找AI时代高薪工作”
- “有什么我能学的高薪岗”
- “skill scan”
- “/skill-scan”
Requirements
- Pre-approved tools (allowed-tools): Bash(*), Read, Write, Edit, Glob, WebSearch, WebFetch, Skill
Workflow steps
9 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 780a8d1. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
Bash(*)ReadWriteEditGlobWebSearchWebFetchSkill
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
node
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
zhipin.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Skill Scan loads about 1.2k tokens when it runs. Until then it costs about 62 tokens; SKILL.md has 313 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Bash(*), Read, Write, Edit, Glob, WebSearch, WebFetch, Skill
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from XBuilderLAB/cheat-on-skill at commit 780a8d1, republished under its MIT licence (© XBuilderLAB). 313 words, ~1,244 tokens.
Download SKILL.mdSave it as
.claude/skills/skill-scan/SKILL.md (or your agent's skills folder).- name
- skill-scan
- description
- cheat-on-skill 的核心。连 BOSS 直聘真实招聘数据 + 网页信号，按用户能力画像找「高薪 × 你学得动 × AI 增强」交集里的候选岗位。每个岗位给：薪资量级 / 需求热度 / 你的差距 / 可学性分 / 诚实学习周期，并过 AI 影响分类与反诈红线。触发词："帮我找岗位"/"找AI时代高薪工作"/"有什么我能学的高薪岗"/"skill scan"/"扫一遍招聘"。前置：需要 .skill-state.json（无则先路由到 skill-init）。
- allowed-tools
- Bash(*), Read, Write, Edit, Glob, WebSearch, WebFetch, Skill
- argument-hint
- [可选：限定方向，如「AI运营」「AI开发」「行业+AI」]
/skill-scan — 高薪 × 可学 × AI 增强 的交集挖掘（核心）
核心方法（先读这条）
不搜"AI 高薪职业 Top10"那类水文——它们利益不中立，是卖课/培训机构的获客漏斗。 真正诚实的需求信号是 BOSS 直聘的真实在招岗位：某岗位在招、给得起价 = 有人真在花钱买这个能力； 岗位数涨=需求升，降=红海。再叠加你的能力画像，挑出"高薪 × 你学得动 × AI 时代仍要"三个圈的交集。
铁律
- 主信源是真实招聘数据（BOSS adapter + 招聘趋势），"职业推荐"水文不作依据。
- 绝不凭记忆。薪资量级、岗位热度、技能要求一律实时取（BOSS / 网页检索加年份）。
- 每个岗位先过 AI 影响分类（
ai-impact-taxonomy.md）：替代型直接劝退，只推增强 / 新生。 - 每个岗位按用户起点算可学性（
learnability-rubric.md），低于阈值不列为首选。 - 按档位收敛（
role-tiers.md）：别给 S0 推够不着的算法岗，别给 S3 推标注。 - 任何带"培训/内推/包就业"的机会过反诈（
anti-scam-rubric.md）。 - 诚实标注 BOSS 数据边界：薪资数字被字体混淆（▯ 占位），只拿到量级；精确值要用户手动看详情页。
- 详情页只读需用户点名：只读取用户明确选择的详情链接；用户可以从候选里选任意数量，也可以少选或不选。读取时保持低频顺序执行，只提取岗位标题、公司、薪资、地点/地址、JD/要求文本；不读取/保存 HR 信息，不点"立即沟通"，不做无选择的批量抓取。
流程
Step 0 — 读上下文
- 读
.skill-state.json拿画像 +profile.start_tier（无 → 路由skill-init）。 - 读
../../shared-references/role-tiers.md（按档位分流）。 - 读
../../shared-references/ai-impact-taxonomy.md（方向闸门）。 - 读
../../shared-references/learnability-rubric.md（可学性打分）。 - 读
../../shared-references/anti-scam-rubric.md（反诈，用于培训/内推类）。 - 读
lessons.md（若存在）：用户过往复盘沉淀，优先参考。 - 任何写入
found_at/found_at_full前，先用系统时间取当前时间：
date '+%Y-%m-%d %H:%M %Z %z'found_at 写日期，found_at_full 写具体时间和时区，跟用户系统时区走（例：2026-06-26 22:06 CST +0800）。对用户展示时写成 2026-06-26 22:06（本机时区 + UTC 偏移，如 中国标准时间 CST，UTC+8），不要写死成某个固定国家的时间。
Step 1 — 按档位锁定搜索词
先按 start_tier 限定方向范围（role-tiers），再结合用户可迁移能力，列 3–6 个 BOSS 搜索关键词。
- S0 →
AI内容运营AIGC运营AI标注数字人运营AI客服 - S1 →
AIGC运营AI营销Prompt工程AI设计AI视频 - S2 →
AI应用开发LLM应用大模型应用AI工程Agent开发 - S3 →
<用户行业>AIAI解决方案行业AI产品AI合规
结合用户的 transferable 能力调词，别用模板硬套。把要搜的词先念给用户确认。
Step 2 — 取真实招聘数据（BOSS adapter，human-in-the-loop）
用 ../../adapters/boss。这是半自动、需用户配合的，先把步骤告诉用户：
cd ../../adapters/boss # 相对 skill 目录；实际路径见安装位置
./launch-chrome.sh # 起【有界面】Chrome，用户扫码登录 BOSS，弹滑块手动过
node diagnose-cdp.mjs 9222 # 可选：确认当前环境能读 Chrome 调试端口
node read-boss.mjs "AIGC运营" 100010000 9222 1 # 搜词读第 1 页列表 → JSON（城市码默认全国）
node read-boss-detail.mjs 9222 "https://www.zhipin.com/job_detail/..." # 用户明确选中后，只读选中的 JD- 每个关键词跑一次，拿回 JSON（岗位名 / 薪资量级 / 公司 / 列表页标签 / 详情链接 / diagnostics）。列表页标签通常只够判断经验/学历/实习周期，完整技能要求仍需用户手动贴 JD。
- 薪资是
▯▯-▯▯K量级（BOSS 字体混淆，adapter 不破解）——位数结构泄露量级，够区分档位；要精确值让用户手动开 2–3 个详情页看。 - JD 真实要求列表页拿不到：先看列表页筛候选，给用户 2–5 条值得看的岗位；用户明确说"读取这几个 JD"后，才用
read-boss-detail.mjs读取 1–3 个详情页。若详情读取失败，再让用户手动贴 JD。 - 若
diagnostics.maybeNeedLogin/blocked/cardCount=0：提示用户登录/过验证/重跑；选择器腐烂就把 diagnostics 发回校准。 - 若连接不上
127.0.0.1:9222：先跑node diagnose-cdp.mjs 9222。若普通终端可读但 Codex/Claude 沙箱内不可读，说明需要非沙箱权限读取本机 Chrome 调试端口，不代表 adapter 选择器坏了。 - ⚠️ 低频、只读列表页，不翻页/不进详情/不私聊（反爬风控 + ToS + 反诈 A6）。
若用户当下不方便登录跑 adapter：退而用 WebSearch 搜"<岗位> 招聘 要求 薪资 2026 / 行情报告"，但明确标注这是二手转述、不如 BOSS 一手。
Step 2.5 — 逐页筛选节奏（最多 3 页）
不要一次性把 BOSS 搜索结果全读完。按下面节奏推进：
- 读取当前关键词第 N 页列表（从第 1 页开始）。
- 用用户画像 + 反诈 rubric 粗筛，向用户提供 2–5 条"值得打开 JD"的候选，并说明为什么；同时点名明显劝退项（如零经验高薪、提成、培训、获客、金融外呼）。
- 每看完一页都提示用户可以调整筛选要求（如不要实习、只看深圳、排除销售/提成、薪资下限、只看全职、只看英文/海外方向）。若用户调整要求，后续页面按新要求筛。
- 等用户明确选择后，调用
read-boss-detail.mjs读取详情页。用户可以选择候选里的任意数量，也可以少选或不选；没有明确选择就不要读详情。一次选择较多时，顺序低频读取并在输出中分批整理，避免并发/高频触发风控。 - 基于 JD 做差距分析和可学性初判。已经读过/用户选过的岗位，后续页面不再重复推荐，只在最终总结里统一回顾。
- 用户完成第二轮选择并读完 JD 后，如果已经积累了足够多可比较岗位（通常 4–8 个 JD 或 2–3 个清晰方向），主动提示可以现在生成阶段报告/岗位报告；用户也可以选择继续看第 3 页。
- 继续下一页，直到看完 3 页、用户要求停止、或已经找到足够强的 2–3 个候选方向。
- 看完最多 3 页后，给用户一个阶段总结：已看页数、候选岗位、已读 JD、待读 JD、劝退模式、用户中途调整过的筛选要求、推荐下一步。
Step 3 — 网页交叉验证 AI 影响与趋势
对每个候选岗位，按 ai-impact-taxonomy.md 判增强/新生/替代：
- 看 BOSS 同词岗位数量量级（涨/缩）。
- WebSearch（加年份）：
<岗位> 招聘趋势 2026、<岗位> 会不会被AI取代、行业用工报告（只用利益中立来源）。 - 替代型直接标"劝退"，即使现在还有岗。
Step 4 — 对每个候选岗位算可学性（核心增量）
按 learnability-rubric.md 的 L1–L5 打分（0–10），结合 JD 要求 vs 用户 transferable：
- 列你的差距（缺哪几块，逐条；哪些可迁移）。
- 给 可学性分 + 判定（高可学/中等/吃力/劝退）。
- 给诚实周期：以用户每周 N 小时算，大概几个月到能投简历。
Step 5 — 反诈过滤（仅对培训/内推/外包类）
若某条路径牵涉付费培训/内推/包就业，过 anti-scam-rubric.md，标判定。岗位本身（公司直招）一般不触红线，但若公司查无此人/JD 零门槛高薪等命中 B 信号，也如实标。
Step 6 — 输出（每个候选岗位用统一格式）
岗位：<名称>
AI 影响：增强 ⬆️ / 新生 🆕 / 替代 ⬇️
薪资量级：<▯ 量级 + 单位>（精确值需手动看详情页）
需求热度：<同词岗位量级/趋势 + 来源年份>
你的差距：<逐条；可迁移的标出来>
可学性：x/10（L1–L5 一句话）
判定：✅ 高可学 / ⚠️ 中等 / ⛔ 吃力 / ❌ 劝退
诚实周期：<以每周 N 小时算，几个月到能投简历>按可学性 × 薪资综合排序，首推 2–3 个交集岗位，劝退的也列出来并说明为什么（避免用户自己踩）。
Step 7 — 落盘
把候选岗位写入 .skill-state.json 的 candidate_roles[]（含 ai_impact / salary_band / demand / gap / learnability_score / learnability_verdict / honest_timeline / scam_verdict / found_at=今天日期 / found_at_full=具体时间和时区 / status=candidate）。
提示用户："我选 XX 这个岗位做学习计划" → 走 skill-plan。
© XBuilderLAB, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/skill-scan of XBuilderLAB/cheat-on-skill.
Open the folder on GitHubat commit 780a8d1
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in XBuilderLAB/cheat-on-skill, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Skill Scan next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Skill Scan this skillXBuilderLAB/cheat-on-skill | 194 | 1 repos | ~1.2k | Automated safety check: Notes | MIT | |
| DeepTutor CLIHKUDS/DeepTutor | 41k | — | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| Zhang Xuefeng Perspectivealchaincyf/zhangxuefeng-skill | 10k | 1 repos | ~2.6k | Automated safety check: Pass | MIT | |
| Deep Reading Analystginobefun/deep-reading-analyst-skill | 353 | 5 repos | ~3.6k | Automated safety check: Pass | MIT | |
| AI Engineering Placement Quizrohitg00/ai-engineering-from-scratch | 66k | — | ~2k | Automated safety check: Pass | MIT | |
| OpenMAIC Setup and ExtensionTHU-MAIC/OpenMAIC | 40k | — | ~1.7k | Automated safety check: Notes | MIT |
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Answers education and career questions in the voice of Zhang Xuefeng, looking up current employment and admissions data before giving a direct verdict.
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Comprehensive framework for deep analysis of articles, papers, and long-form content using 10+ thinking models (SCQA, 5W2H, critical thinking, inversion, mental models, first principles, systems…
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Questions about Skill Scan
What does Skill Scan do?
cheat-on-skill 的核心。连 BOSS 直聘真实招聘数据 + 网页信号，按用户能力画像找「高薪 × 你学得动 × AI 增强」交集里的候选岗位。每个岗位给：薪资量级 / 需求热度 / 你的差距 / 可学性分 / 诚实学习周期，并过 AI 影响分类与反诈红线。触发词："帮我找岗位"/"找AI时代高薪工作"/"有什么我能学的高薪岗"/"skill scan"/"扫一遍招聘"。前置：需要…. Skill Scan is an agent skill from XBuilderLAB/cheat-on-skill.
When should I use Skill Scan?
Skill Scan fits situations like: education work in your project.
How do I install Skill Scan in Claude Code?
Run `npx skills add XBuilderLAB/cheat-on-skill --skill skill-scan -a claude-code`. Or copy the skill folder (skills/skill-scan in XBuilderLAB/cheat-on-skill) into .claude/skills/skill-scan in your project. Claude Code loads it when a task matches its description.
How do I install Skill Scan in Codex?
Run `npx skills add XBuilderLAB/cheat-on-skill --skill skill-scan -a codex`. Or copy the skill folder (skills/skill-scan in XBuilderLAB/cheat-on-skill) into .agents/skills/skill-scan in your project. Codex loads it when a task matches its description.
Can I use Skill Scan in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add XBuilderLAB/cheat-on-skill --skill skill-scan -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skill-scan, .gemini/skills/skill-scan, .github/skills/skill-scan and .opencode/skills/skill-scan in your project.
What does Skill Scan need to run?
Going by SKILL.md and its folder, Skill Scan needs the command-line tools its instructions call (node). Its frontmatter pre-approves these tools: Bash(*), Read, Write, Edit, Glob, WebSearch, WebFetch, Skill.
Does Skill Scan access the network?
SKILL.md names 1 domain. In commands or code: zhipin.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Skill Scan safe to install?
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Skill Scan use?
Skill Scan is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Skill Scan use?
About 1.2k tokens (SKILL.md is roughly 5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Skill Scan?
Skills that share tags, products or a category with Skill Scan: DeepTutor CLI (HKUDS/DeepTutor, 41k stars), Zhang Xuefeng Perspective (alchaincyf/zhangxuefeng-skill, 10k stars), Deep Reading Analyst (ginobefun/deep-reading-analyst-skill, 353 stars) and AI Engineering Placement Quiz (rohitg00/ai-engineering-from-scratch, 66k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Skill Scan?
XBuilderLAB (a GitHub organization) maintains it in XBuilderLAB/cheat-on-skill, which has 194 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on June 27, 2026.
Source: XBuilderLAB/cheat-on-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.