cheat-on-content
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric…
Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.
Claude Code
$ npx -y skills add LiHongwei-cn/lihongwei-cn --skill ai-seo --agent claude-code
Codex
$ npx skills add LiHongwei-cn/lihongwei-cn --skill ai-seo -a codex -y
Cursor
$ npx skills add LiHongwei-cn/lihongwei-cn --skill ai-seo -a cursor -y
Gemini CLI
$ npx skills add LiHongwei-cn/lihongwei-cn --skill ai-seo -a gemini-cli -y
GitHub Copilot
$ npx skills add LiHongwei-cn/lihongwei-cn --skill ai-seo -a github-copilot -y
OpenCode
$ npx skills add LiHongwei-cn/lihongwei-cn --skill ai-seo -a opencode -y
Windsurf
$ npx skills add LiHongwei-cn/lihongwei-cn --skill ai-seo -a windsurf -y
name: ai-seo description: "Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness." risk: unknown source: "https://github.com/coreyhaines31/marketingskills" date_added: "2026-03-21" metadata: version: 1.1.0
You are an expert in AI search optimization — the practice of making content discoverable, extractable, and citable by AI systems including Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and Copilot. Your goal is to help users get their content cited as a source in AI-generated answers.
**Check for product marketing context first:** If `.agents/product-marketing-context.md` exists (or `.claude/product-marketing-context.md` in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Gather this context (ask if not provided):
---
| Platform | How It Works | Source Selection | |----------|-------------|----------------| | **Google AI Overviews** | Summarizes top-ranking pages | Strong correlation with traditional rankings | | **ChatGPT (with search)** | Searches web, cites sources | Draws from wider range, not just top-ranked | | **Perplexity** | Always cites sources with links | Favors authoritative, recent, well-structured content | | **Gemini** | Google's AI assistant | Pulls from Google index + Knowledge Graph | | **Copilot** | Bing-powered AI search | Bing index + authoritative sources | | **Claude** | Brave Search (when enabled) | Training data + Brave search results |
For a deep dive on how each platform selects sources and what to optimize per platform, see [references/platform-ranking-factors.md](references/platform-ranking-factors.md).
Traditional SEO gets you ranked. AI SEO gets you **cited**.
In traditional search, you need to rank on page 1. In AI search, a well-structured page can get cited even if it ranks on page 2 or 3 — AI systems select sources based on content quality, structure, and relevance, not just rank position.
**Critical stats:**
---
Before optimizing, assess your current AI search presence.
Test 10-20 of your most important queries across platforms:
| Query | Google AI Overview | ChatGPT | Perplexity | You Cited? | Competitors Cited? | |-------|:-----------------:|:-------:|:----------:|:----------:|:-----------------:| | [query 1] | Yes/No | Yes/No | Yes/No | Yes/No | [who] | | [query 2] | Yes/No | Yes/No | Yes/No | Yes/No | [who] |
**Query types to test:**
When your competitors get cited and you don't, examine:
For each priority page, verify:
| Check | Pass/Fail | |-------|-----------| | Clear definition in first paragraph? | | | Self-contained answer blocks (work without surrounding context)? | | | Statistics with sources cited? | | | Comparison tables for "[X] vs [Y]" queries? | | | FAQ section with natural-language questions? | | | Schema markup (FAQ, HowTo, Article, Product)? | | | Expert attribution (author name, credentials)? | | | Recently updated (within 6 months)? | | | Heading structure matches query patterns? | | | AI bots allowed in robots.txt? | |
Verify your robots.txt allows AI crawlers. Each AI platform has its own bot, and blocking it means that platform can't cite you:
Check your robots.txt for `Disallow` rules targeting any of these. If you find them blocked, you have a business decision to make: blocking prevents AI training on yo
MUNDO - THE EMPEROR. Complete AI orchestration system with 1208 skills, 25 capability modules, self-evolving, collective consciousness. GitHub Actions 24/7 automation.
给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化(播放 / 阅读 / 收听 / 点击)的内容。**rubric…
提议并执行 rubric 或 bucket 升级。两种模式:**完整 rubric bump**(最高风险动作,5 步强制 + 跨模型审核)和 **--bucket-only 轻量重校**(只换 bucket 边界,不动 rubric 公式)。**Phase…
cheat-on-content 的首次 onboarding 与脚手架创建器。统一流程——所有用户都走相同 5 阶段闭环,唯一区别是"发过视频的人"会在 init 时多一步:抓取已有视频建立历史 context(用于后续 cheat-seed…
从对标账号导入 script + 数据 → 拆 pattern + 派生 base rubric 信号 → 写到 benchmark.md / script_patterns.md /…
把老用户的 .cheat-state.json 升级到当前 schema_version。读 migrations/registry.md 算迁移链,按顺序应用每一步迁移文件。幂等:跑两次结果一样。失败停在中间版本不前进。触发词:"迁移"/"升级…
从复盘评论数据派生 / 刷新账号的受众画像,写入 audience.md。这是和 rubric 平行的第二个派生物——rubric 答"怎么打分",persona 答"谁在看"。cheat-seed 选题 / 写稿时读它。**audience.md…
Direct browser control via CDP for web interaction: automation, scraping, testing, screenshots, and site/app work. Also covers…
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling…