Geo Fundamentals
wasp-lang/wasp
Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).
使用 Bing Webmaster 页面与查询数据、索引状态、产品结果和 Bing AI Performance 证据复盘 SEO 页面，诊断收录、排名、点击率、意图、内容、转化和 AI 引用问题。需要比较周期表现、分析 citations、cited pages、grounding queries、query fan-out 或决定下一步 SEO/GEO 行动时使用。
Install Review SEO Performance
$ npx skills add tsingyuai/growth-lab --skill review-seo-performance -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install tsingyuai/growth-lab review-seo-performance --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/tsingyuai/growth-lab.git skills-src && mkdir -p .claude/skills && cp -r skills-src/executors/review-seo-performance .claude/skills/review-seo-performance && 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 "review-seo-performance" agent skill from https://github.com/tsingyuai/growth-lab/tree/main/executors/review-seo-performance into .claude/skills/review-seo-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-seo-performance", 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/tsingyuai/growth-lab/tree/main/executors/review-seo-performanceType 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 tsingyuai/growth-lab --skill review-seo-performance -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install tsingyuai/growth-lab review-seo-performance --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tsingyuai/growth-lab.git skills-src && mkdir -p .agents/skills && cp -r skills-src/executors/review-seo-performance .agents/skills/review-seo-performance && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "review-seo-performance" agent skill from https://github.com/tsingyuai/growth-lab/tree/main/executors/review-seo-performance into .agents/skills/review-seo-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-seo-performance", 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 tsingyuai/growth-lab --skill review-seo-performance -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install tsingyuai/growth-lab review-seo-performance --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tsingyuai/growth-lab.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/executors/review-seo-performance .cursor/skills/review-seo-performance && 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 "review-seo-performance" agent skill from https://github.com/tsingyuai/growth-lab/tree/main/executors/review-seo-performance into .cursor/skills/review-seo-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-seo-performance", 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/tsingyuai/growth-lab.git --path executors/review-seo-performance--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 tsingyuai/growth-lab --skill review-seo-performance -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install tsingyuai/growth-lab review-seo-performance --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tsingyuai/growth-lab.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/executors/review-seo-performance .gemini/skills/review-seo-performance && 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 "review-seo-performance" agent skill from https://github.com/tsingyuai/growth-lab/tree/main/executors/review-seo-performance into .gemini/skills/review-seo-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-seo-performance", 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 tsingyuai/growth-lab review-seo-performanceInstalls 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 tsingyuai/growth-lab --skill review-seo-performance -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/tsingyuai/growth-lab.git skills-src && mkdir -p .github/skills && cp -r skills-src/executors/review-seo-performance .github/skills/review-seo-performance && 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 "review-seo-performance" agent skill from https://github.com/tsingyuai/growth-lab/tree/main/executors/review-seo-performance into .github/skills/review-seo-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-seo-performance", 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 tsingyuai/growth-lab --skill review-seo-performance -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install tsingyuai/growth-lab review-seo-performance --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tsingyuai/growth-lab.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/executors/review-seo-performance .opencode/skills/review-seo-performance && 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 "review-seo-performance" agent skill from https://github.com/tsingyuai/growth-lab/tree/main/executors/review-seo-performance into .opencode/skills/review-seo-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-seo-performance", 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
review-seo-performance- GitHub stars
- 2k
- Token cost
- ~610 tokens
- SKILL.md length
- 156 words
- Files
- 2
- Skills in repo
- 22
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
使用 Bing Webmaster 页面与查询数据、索引状态、产品结果和 Bing AI Performance 证据复盘 SEO 页面，诊断收录、排名、点击率、意图、内容、转化和 AI 引用问题。需要比较周期表现、分析 citations、cited pages、grounding queries、query fan-out 或决定下一步 SEO/GEO 行动时使用。
- Works in 5 steps: 聚合重复出现的概念、对象、比较维度和任务。 → 区分自然查询与程序化查询。 → 找出频繁触发检索但当前页面引用弱或没有覆盖的概念。 → …
- Tasks that involve AI search optimization
- SKILL.md covers 收集传统搜索证据, 收集 Bing AI Performance, 诊断主要约束 and 输出复盘
- Calls node
What it does
Review SEO Performance is an agent skill from tsingyuai/growth-lab. 使用 Bing Webmaster 页面与查询数据、索引状态、产品结果和 Bing AI Performance 证据复盘 SEO 页面，诊断收录、排名、点击率、意图、内容、转化和 AI 引用问题。需要比较周期表现、分析 citations、cited pages、grounding queries、query fan-out 或决定下一步 SEO/GEO 行动时使用。
Its SKILL.md is about 610 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).
It sits in Marketing & SEO, covering AI search optimization. The repository describes itself as: An end-to-end growth tool that understands the product, fetch the data it needs, researches the market, executes campaigns, and reviews results to improve the next round of… The licence is Apache-2.0.
When your agent uses it
- Tasks that involve AI search optimization
Example prompts
- “/review-seo-performance”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- 聚合重复出现的概念、对象、比较维度和任务。
- 区分自然查询与程序化查询。
- 找出频繁触发检索但当前页面引用弱或没有覆盖的概念。
- 判断它应成为现有页面的新段落、比较表、FAQ、独立页面还是不值得处理的旁支。
- 回到实时 SERP 和产品能力验证，不因 AI 查询出现就自动创建页面。
What it can do on your machine
Read from SKILL.md and the folder at commit 2d0807c. 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
Shell commands in SKILL.md call:
node
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
Review SEO Performance loads about 610 tokens when it runs. Until then it costs about 52 tokens; SKILL.md has 156 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 tsingyuai/growth-lab at commit 2d0807c, republished under its Apache-2.0 licence (© tsingyuai). 156 words, ~610 tokens.
Download SKILL.mdSave it as
.claude/skills/review-seo-performance/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- review-seo-performance
- description
- 使用 Bing Webmaster 页面与查询数据、索引状态、产品结果和 Bing AI Performance 证据复盘 SEO 页面，诊断收录、排名、点击率、意图、内容、转化和 AI 引用问题。需要比较周期表现、分析 citations、cited pages、grounding queries、query fan-out 或决定下一步 SEO/GEO 行动时使用。
复盘 SEO 与 AI 可见性
用可比较周期和页面原始目标复盘已发布页面。考虑上线日期、季节性、抓取与收录延迟，把证据与解释分开。
收集传统搜索证据
node collectors/bing-webmaster/bing-webmaster.mjs page-stats \
--site "$SITE_URL" --out <page-stats-file>
node collectors/bing-webmaster/bing-webmaster.mjs page-query-stats \
--site "$SITE_URL" --page "$PAGE_URL" --out <query-stats-file>
node collectors/bing-webmaster/bing-webmaster.mjs url-info \
--site "$SITE_URL" --url "$PAGE_URL"读取：
- 抓取与索引状态；
- 展现、查询、点击和点击率；
- 平均展现位置与点击位置；
- 页面或摘要更新前后的变化；
- 产品动作、激活、收入或当前产品真正关心的结果；
- 相关 Memory 中的基线和历史行动。
收集 Bing AI Performance
Bing Webmaster Tools 的 AI Performance 主要通过网页界面提供。使用已登录浏览器读取：
| 指标 | 含义 |
|---|---|
| Total Citations | 页面内容在 AI 答案中作为来源出现的总次数 |
| Cited Pages | 被 AI 当作来源的页面数量与时间变化 |
| Page-level citations | 具体 URL 的被引用次数 |
| Grounding Queries | AI 为寻找引用材料实际运行的检索短语 |
Grounding queries 与传统人类关键词不同。用户的一句话会被模型拆成多个查询，这就是 query fan-out。程序化查询常出现比较、评估、监控、标准、优缺点等结构，它们可以揭示传统关键词工具看不到的内容需求。
AI Performance 的产品状态和字段可能变化，grounding queries 没有稳定 API 时以 Bing Webmaster Tools 当前网页界面为准。只报告界面实际提供的数据，不把推测的合作方覆盖范围写成官方承诺。
用 Grounding queries 反推内容
- 聚合重复出现的概念、对象、比较维度和任务。
- 区分自然查询与程序化查询。
- 找出频繁触发检索但当前页面引用弱或没有覆盖的概念。
- 判断它应成为现有页面的新段落、比较表、FAQ、独立页面还是不值得处理的旁支。
- 回到实时 SERP 和产品能力验证，不因 AI 查询出现就自动创建页面。
检查可提取性
- 高频 grounding 术语是否出现在对应 H2 与前一到两段；
- 结论是否前置，段落能否独立理解；
- 表格、FAQ、步骤和定义是否便于准确抽取；
- 数据、示例和来源是否足以支撑引用；
- 页面是否有作者、更新时间和相邻主题覆盖；
- schema.org、canonical、robots、sitemap 与 IndexNow 是否正确。
- 站点需要面向 LLM 提供内容导航时，检查
llms.txt是否准确、可访问并只声明真实公开内容；不要把它当成收录或引用保证。
三层验证
- 服务器日志：区分 BingBot、OAI-SearchBot 等机器访问和真实用户访问。
- 查询模式：比较传统搜索查询与 AI Performance 的程序化 grounding queries。
- 产品结果：把引用和搜索可见性与分析工具中的来源、访问和产品动作对照。
引用多、点击少不等于失败，也不等于成功。它表示内容被 AI 使用但没有形成等量访问，需要结合品牌呈现、用户后续动作和产品目标判断。
诊断主要约束
- 发现：目标 canonical 尚未被抓取或收录。
- 需求：目标词族没有足够可观察需求。
- 排名：有展现但位置弱。
- 摘要：位置有竞争力但点击率弱。
- 意图：实际到达查询与页面任务偏离。
- 内容：竞品提供更强证据、工具、信息增益、新鲜度或清晰度。
- 转化：页面满足搜索意图但没有带来相应产品行动。
- 有引用无访问：AI 系统使用内容，但用户很少继续访问或识别品牌。
输出复盘
需要视觉比较时，在当前 Model 的 Memory 生成独立 HTML，包含适合当前证据的周期比较、查询表、位置分布、产品结果、AI 引用、grounding query 分类和标注结论。原始导出放在同一 Memory 下。
推荐一个首要下一步，并说明验证它的证据：
- 加强当前页面；
- 修改 title 和摘要；
- 补充缺失证据、工具或信息增益；
- 调整转化路径；
- 新建支持页面；
- 修复收录、canonical 或发现问题；
- 增强 AI 可提取性；
- 等待一个明确观察窗口。
© tsingyuai, 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 1 other file in executors/review-seo-performance of tsingyuai/growth-lab.
- SKILL.md
- agents/openai.yaml
Open the folder on GitHubat commit 2d0807c
Compare with similar skills
Review SEO Performance 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 |
|---|---|---|---|---|---|---|
| Review SEO Performance this skilltsingyuai/growth-lab | 2k | — | ~610 | Automated safety check: Pass | Apache-2.0 | |
| Geo Fundamentalswasp-lang/wasp | 19k | 9 repos | ~861 | Automated safety check: Pass | MIT | |
| SEO GeoReScienceLab/opc-skills | 1.8k | 4 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| GEO-First SEO Audit Toolzubair-trabzada/geo-seo-claude | 11k | — | ~2.8k | Automated safety check: Notes | MIT | |
| GEO Monthly Delta Reportzubair-trabzada/geo-seo-claude | 11k | — | ~2.4k | Automated safety check: Notes | MIT | |
| SEO DataforseoAgriciDaniel/codex-seo | 799 | 2 repos | ~4.6k | Automated safety check: Pass | MIT |
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Categories
Questions about Review SEO Performance
What does Review SEO Performance do?
使用 Bing Webmaster 页面与查询数据、索引状态、产品结果和 Bing AI Performance 证据复盘 SEO 页面，诊断收录、排名、点击率、意图、内容、转化和 AI 引用问题。需要比较周期表现、分析 citations、cited pages、grounding queries、query fan-out 或决定下一步 SEO/GEO 行动时使用。. Review SEO Performance is an agent skill from tsingyuai/growth-lab.
When should I use Review SEO Performance?
Review SEO Performance fits situations like: tasks that involve AI search optimization.
How do I install Review SEO Performance in Claude Code?
Run `npx skills add tsingyuai/growth-lab --skill review-seo-performance -a claude-code`. Or copy the skill folder (executors/review-seo-performance in tsingyuai/growth-lab) into .claude/skills/review-seo-performance in your project. Claude Code loads it when a task matches its description.
How do I install Review SEO Performance in Codex?
Run `npx skills add tsingyuai/growth-lab --skill review-seo-performance -a codex`. Or copy the skill folder (executors/review-seo-performance in tsingyuai/growth-lab) into .agents/skills/review-seo-performance in your project. Codex loads it when a task matches its description.
Can I use Review SEO Performance 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 tsingyuai/growth-lab --skill review-seo-performance -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review-seo-performance, .gemini/skills/review-seo-performance, .github/skills/review-seo-performance and .opencode/skills/review-seo-performance in your project.
What does Review SEO Performance need to run?
Going by SKILL.md and its folder, Review SEO Performance needs the command-line tools its instructions call (node).
Does Review SEO Performance 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 Review SEO Performance 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 Review SEO Performance use?
Review SEO Performance 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 Review SEO Performance use?
About 610 tokens (SKILL.md is roughly 2.4k 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 Review SEO Performance?
Skills that share tags, products or a category with Review SEO Performance: Geo Fundamentals (wasp-lang/wasp, 19k stars), SEO Geo (ReScienceLab/opc-skills, 1.8k stars), GEO-First SEO Audit Tool (zubair-trabzada/geo-seo-claude, 11k stars) and GEO Monthly Delta Report (zubair-trabzada/geo-seo-claude, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Review SEO Performance?
tsingyuai (a GitHub organization) maintains it in tsingyuai/growth-lab, which has 2,000 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on September 28, 2026.
Source: tsingyuai/growth-lab on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.