Code Review Checklist
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
创作者/品牌入驻：通过结构化访谈收集视觉风格、内容调性、受众画像和运营目标，生成完整的账号画像档案. An agent skill from ZJU-REAL/Easel.
Install Skill Brand Onboarding
$ npx skills add ZJU-REAL/Easel --skill skill-brand-onboarding -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ZJU-REAL/Easel skill-brand-onboarding --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/ZJU-REAL/Easel.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/openclaw/skill-brand-onboarding .claude/skills/skill-brand-onboarding && 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-brand-onboarding" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-brand-onboarding into .claude/skills/skill-brand-onboarding/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-brand-onboarding", 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/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-brand-onboardingType 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 ZJU-REAL/Easel --skill skill-brand-onboarding -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ZJU-REAL/Easel skill-brand-onboarding --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/openclaw/skill-brand-onboarding .agents/skills/skill-brand-onboarding && 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-brand-onboarding" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-brand-onboarding into .agents/skills/skill-brand-onboarding/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-brand-onboarding", 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 ZJU-REAL/Easel --skill skill-brand-onboarding -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ZJU-REAL/Easel skill-brand-onboarding --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/openclaw/skill-brand-onboarding .cursor/skills/skill-brand-onboarding && 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-brand-onboarding" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-brand-onboarding into .cursor/skills/skill-brand-onboarding/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-brand-onboarding", 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/ZJU-REAL/Easel.git --path skills/openclaw/skill-brand-onboarding--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 ZJU-REAL/Easel --skill skill-brand-onboarding -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ZJU-REAL/Easel skill-brand-onboarding --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/openclaw/skill-brand-onboarding .gemini/skills/skill-brand-onboarding && 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-brand-onboarding" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-brand-onboarding into .gemini/skills/skill-brand-onboarding/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-brand-onboarding", 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 ZJU-REAL/Easel skill-brand-onboardingInstalls 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 ZJU-REAL/Easel --skill skill-brand-onboarding -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/openclaw/skill-brand-onboarding .github/skills/skill-brand-onboarding && 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-brand-onboarding" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-brand-onboarding into .github/skills/skill-brand-onboarding/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-brand-onboarding", 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 ZJU-REAL/Easel --skill skill-brand-onboarding -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ZJU-REAL/Easel skill-brand-onboarding --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ZJU-REAL/Easel.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/openclaw/skill-brand-onboarding .opencode/skills/skill-brand-onboarding && 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-brand-onboarding" agent skill from https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-brand-onboarding into .opencode/skills/skill-brand-onboarding/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-brand-onboarding", 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-brand-onboarding- GitHub stars
- 3.4k
- Token cost
- ~704 tokens
- SKILL.md length
- 203 words
- Files
- 3 (incl. references)
- Skills in repo
- 114
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
创作者/品牌入驻：通过结构化访谈收集视觉风格、内容调性、受众画像和运营目标，生成完整的账号画像档案. An agent skill from ZJU-REAL/Easel.
- Works in 6 steps: 环境准备 → 信息采集 → 预填访谈文档 → …
- Tasks that involve Performance optimization
- SKILL.md covers 输入, 输出, Phase 0 — 环境准备 and Phase 1 — 信息采集, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Skill Brand Onboarding is an agent skill from ZJU-REAL/Easel. 创作者/品牌入驻：通过结构化访谈收集视觉风格、内容调性、受众画像和运营目标，生成完整的账号画像档案。 当用户说"账号入驻""建档案""新账号建立画像""品牌入驻""从零建号""完善账号信息""onboarding"时使用。 产出覆盖多维度的完整账号档案；只建声音画像用 skill-voice-builder，只建受众画像用 skill-audience-profiler。
Its SKILL.md is about 700 tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `EASEL-META.md` and `references/profile-templates.md`).
It sits in Development, covering Performance optimization. The repository describes itself as: An open-source AI agent for social media — discover trends, create content, publish everywhere, and learn what works across Xiaohongshu, Douyin, Zhihu, Bilibili, and more.🎨一个开源的… The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Performance optimization
Example prompts
- “新账号建立画像”
- “完善账号信息”
- “onboarding”
- “/skill-brand-onboarding”
Workflow steps
6 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 278f420. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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 Brand Onboarding loads about 704 tokens when it runs, and up to ~1.3k if it reads all its reference files. Until then it costs about 53 tokens; SKILL.md has 203 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 passed
The automated check found no risky patterns in SKILL.md.
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 ZJU-REAL/Easel at commit 278f420, republished under its Apache-2.0 licence (© ZJU-REAL). 203 words, ~704 tokens.
Download SKILL.mdSave it as
.claude/skills/skill-brand-onboarding/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- skill-brand-onboarding
- description
- 创作者/品牌入驻：通过结构化访谈收集视觉风格、内容调性、受众画像和运营目标，生成完整的账号画像档案。 当用户说"账号入驻""建档案""新账号建立画像""品牌入驻""从零建号""完善账号信息""onboarding"时使用。 产出覆盖多维度的完整账号档案；只建声音画像用 skill-voice-builder，只建受众画像用 skill-audience-profiler。
- layer
- plan
品牌入驻
通过结构化访谈 + 公开信息采集，为创作者/品牌生成完整的 Easel 账号画像（Profile）。
输入
用户提供品牌/账号名称，以及可选的社媒链接、截图、品牌资料。
输出
profiles/<name>/ 目录，包含：
| 文件 | 内容 |
|---|---|
identity.md | 品牌名、定位、使命、差异化、核心产品/服务 |
style.md | 视觉风格、语气调性、内容节奏、Do/Don't 规则 |
audience.md | 目标人群画像、用户语言、痛点与需求 |
platforms.md | 活跃平台、账号信息、发布频率、标签策略 |
preferences.md | 内容支柱、主推产品、禁区话题、合规底线 |
memory.md | 初始为空，后续由归因层更新 |
Phase 0 — 环境准备
- 询问画像名称（英文小写，用于目录名，如
my-brand） - 检查
profiles/<name>/是否已存在：- 已存在 → 摘要现有内容，询问：更新还是重建？
- 不存在 → 继续
- 确保
profiles/<name>/目录存在
Phase 1 — 信息采集
先采集公开信息，再问用户补缺口。
步骤 1：收集社媒链接
向用户询问（有哪些提供哪些）：
- 小红书 / 抖音 / B站 / 微博主页链接或 ID
- 个人网站 / 公众号名称
- 已有的品牌手册、VI 文件、截图（可提供文件路径）
步骤 2：公开信息提取
对每个链接使用 WebFetch 抓取公开页面，提取：
可确认的事实（标注来源）：
- 品牌名、账号昵称、简介/签名
- 所在地、服务范围
- 产品或服务品类
- 品牌价值观（如简介中有声明）
- 社媒数据：粉丝数、获赞与收藏、笔记/视频数
- 视觉观察：封面风格、滤镜偏好、排版习惯、主色调
WebFetch 无法获取的信息标记为待确认缺口。
仅用户能回答的缺口：
- 精确品牌色（hex 值）、字体名称
- 目标人群描述（ICP）
- 主推产品/服务、核心差异化
- 社媒运营目标、当前运营现状
- 标志性内容格式和真实文案示例
- 绝对不做的事
Phase 2 — 预填访谈文档
生成面向用户的访谈文档，写入 outputs/品牌名/品牌入驻.md。
文档四部分：
第一部分 — 我们已经了解的 将 Phase 1 确认的事实以陈述形式呈现，让用户核对纠正。
"以上信息是否准确？有无遗漏或需要纠正的？"
第二部分 — 需要你来回答的（仅真正缺口）
- 目标用户是谁？（ICP）
- 主推产品/服务？
- 和同类账号最大的不同？
- 社媒核心目标？（涨粉 / 带货 / 品牌认知 / 社群 — 选 1-2 个）
- 目前运营节奏？什么效果好/不好？
第三部分 — 素材清单 必须：品牌色值、Logo、产品实拍图（高清原图） 有则更好：场景图、品牌手册、代表性帖子截图、欣赏/想避开的账号
第四部分 — 品牌与内容细节
- 文字排版偏好、标志性内容格式
- 3-5 条真实文案示例（标注"最有价值的输入"）
- 内容支柱（勾选 + 自定义）
- 绝对不发的内容、内容形式比例、近期重要节点
根据品牌调性调整文档语气。
Phase 3 — 素材与回复审核
用户返回填写的文档和素材后：
- 素材处理 — Logo →
profiles/<name>/assets/logo.png；产品图 →assets/products/；场景图 →assets/lifestyle/；示例帖子 →assets/examples/ - 回复整合 — 将用户回答与 Phase 1 采集合并，识别剩余缺口
- 补充确认 — 如有关键缺口，针对性追问（不超过 3 个问题）
Phase 4 — 生成画像档案
将所有信息综合写入 profiles/<name>/ 下各文件。
按 profile-templates.md 中的模板结构生成六个文件：
identity.md— 基本信息、核心产品、差异化、内容方向style.md— 语气调性、视觉风格、标志性格式、文案示例、Do/Don'taudience.md— ICP、用户语言、痛点需求、互动特征platforms.md— 各平台账号数据、内容形式、发布频率、标签preferences.md— 内容支柱、主推产品、禁区、合规底线、运营目标memory.md— 初始为空模板
未获得的信息标记为 [待补充]，不编造。从截图估算的标注 (估算)。
Phase 5 — 确认定稿
向用户展示生成的完整画像，逐文件确认：
- 有没有事实错误？
- 有没有不适用的部分需要删除？
- 有没有遗漏需要补充？
修改完成后确认：
"画像已保存至
profiles/<name>/。Easel 的所有 SKILL 将自动读取此画像。"
操作备注
- 必须先采集公开信息再生成访谈文档 — 预填已知信息体现专业度，用户也能更快完成
- 标志性内容格式和真实文案示例是最重要的输入 — 让生成内容像本人而非通用 AI 的关键
- 品牌色是第二重要的视觉输入 — 色值错了所有视觉产出都不对，估算的标注"(估算)"
- 不编造品牌细节 — 未获得的信息写
[待补充] - 受众和运营目标不能跳过 — 没有 ICP 和目标，后续内容策划都会泛泛而谈
© ZJU-REAL, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files (references) in skills/openclaw/skill-brand-onboarding of ZJU-REAL/Easel.
- SKILL.md
- EASEL-META.md
- references/profile-templates.md
Open the folder on GitHubat commit 278f420
Compare with similar skills
Skill Brand Onboarding 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 Brand Onboarding this skillZJU-REAL/Easel | 3.4k | — | ~704 | Automated safety check: Pass | Apache-2.0 | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 4 repos | ~1.1k | Automated safety check: Pass | MIT | |
| LLM Torch Profiler Analysissgl-project/sglang | 37k | 2 repos | ~6.4k | Automated safety check: Pass | Apache-2.0 | |
| Pycrazyguitar/pysheeet | 8.2k | — | ~886 | Automated safety check: Pass | MIT | |
| Cmux Debugging Guidemanaflow-ai/cmux | 28k | 1 repos | ~1.1k | Automated safety check: Pass | Custom licence | |
| Analyzing .NET Performancedotnet/skills | 5.6k | 3 repos | ~3.1k | Automated safety check: Pass | MIT |
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Questions about Skill Brand Onboarding
What does Skill Brand Onboarding do?
创作者/品牌入驻：通过结构化访谈收集视觉风格、内容调性、受众画像和运营目标，生成完整的账号画像档案. An agent skill from ZJU-REAL/Easel. Skill Brand Onboarding is an agent skill from ZJU-REAL/Easel.
When should I use Skill Brand Onboarding?
Skill Brand Onboarding fits situations like: tasks that involve Performance optimization.
How do I install Skill Brand Onboarding in Claude Code?
Run `npx skills add ZJU-REAL/Easel --skill skill-brand-onboarding -a claude-code`. Or copy the skill folder (skills/openclaw/skill-brand-onboarding in ZJU-REAL/Easel) into .claude/skills/skill-brand-onboarding in your project. Claude Code loads it when a task matches its description.
How do I install Skill Brand Onboarding in Codex?
Run `npx skills add ZJU-REAL/Easel --skill skill-brand-onboarding -a codex`. Or copy the skill folder (skills/openclaw/skill-brand-onboarding in ZJU-REAL/Easel) into .agents/skills/skill-brand-onboarding in your project. Codex loads it when a task matches its description.
Can I use Skill Brand Onboarding 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 ZJU-REAL/Easel --skill skill-brand-onboarding -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-brand-onboarding, .gemini/skills/skill-brand-onboarding, .github/skills/skill-brand-onboarding and .opencode/skills/skill-brand-onboarding in your project.
What does Skill Brand Onboarding need to run?
SKILL.md names no scripts, command-line tools or credentials: Skill Brand Onboarding is instructions for the agent only.
Does Skill Brand Onboarding access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Skill Brand Onboarding safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Skill Brand Onboarding use?
Skill Brand Onboarding is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Skill Brand Onboarding use?
About 704 tokens (SKILL.md is roughly 2.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 614 tokens, read only when the agent opens those files.
What are the alternatives to Skill Brand Onboarding?
Skills that share tags, products or a category with Skill Brand Onboarding: Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), LLM Torch Profiler Analysis (sgl-project/sglang, 37k stars), Py (crazyguitar/pysheeet, 8.2k stars) and Cmux Debugging Guide (manaflow-ai/cmux, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Skill Brand Onboarding?
ZJU-REAL (a GitHub organization) maintains it in ZJU-REAL/Easel, which has 3,376 GitHub stars. The repository holds 114 skills in this directory. The repository was last updated on October 9, 2026.
Source: ZJU-REAL/Easel on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.