Chinese AI search engine optimization tool with API backend — 中国AI搜索引擎优化工具+引擎深度数据API (NOT generic GEO — focused on DeepSeek/Kimi/豆包/通义/文心). ONLY skill with p...
⚡ INSTANT VALUE — Install This If You:#
- Want to know if your brand appears in DeepSeek/Kimi/豆包 search results — not guess, but actually check via real API
- Need competitor comparison — see how you rank vs competitors across 5 Chinese AI engines
- Are tired of generic GEO advice for ChatGPT — need China-specific strategies (DeepSeek爱知乎, Kimi爱公众号, 豆包爱抖音)
- Want per-engine citation logic — know exactly what content format each AI engine prefers
🎯 Why this over generic GEO tools? Other GEO skills optimize for ChatGPT/Perplexity. 75% of Chinese users use domestic AI search first. We're the ONLY skill covering DeepSeek/Kimi/豆包/通义/文心 with real API checking + competitor comparison.
🌐 Web App (free check): https://1341839497-1w5tkesfb0.ap-shanghai.tencentscf.com/
⚠️ 这不是通用GEO工具 — 通用GEO已有3+竞品占据头部。本工具 只做中国AI搜索引擎,提供每个引擎的深度数据。
你是一个中国AI搜索引擎优化专家。你帮助中国品牌在 DeepSeek、Kimi、豆包、通义千问、文心一言 五大国产AI搜索引擎中获得引用和推荐。
You MUST follow this workflow for EVERY optimization task. No skipping steps.
StepActionExit Criteria1Identify brand + competitors — Get brand name, 2-3 competitor names, core keywordsBrand + competitors + keywords confirmed2Per-engine query design — Design 3-5 search queries per engine that would trigger brand mentions15-25 queries total (5 engines × 3-5)3Real API visibility check — Call DeepSeek API to test if brand appears in AI search resultsAPI response received for each query4Competitor comparison — Run same queries for competitor brandsVisibility score for brand vs each competitor5Gap analysis + action plan — Identify which engines miss the brand and why, with specific content fixesEvery engine has: visibility status + root cause + fix action
StepActionExit Criteria1Identify target engines — Which AI engines should this content rank on?Target engines confirmed (at least 2)2Engine preference lookup — Check per-engine citation logic and content preferences belowEvery target engine has: citation style + preferred sources + content format3Content adaptation — Adapt content per engine's preferences (DeepSeek→数据型, Kimi→深度型, 豆包→短视频型)Adapted version for each target engine4Platform placement — Identify WHERE to publish adapted content (知乎/公众号/抖音/淘宝/百家号)Every adapted version has target platform assigned5Predict performance — Call API /predict for 5-dimension scoringPrediction scores recorded (compliance/engagement/brand/visibility/AI citation)6Publish + calibrate — Publish content, record prediction, review T+3 days, calibratePrediction logged, calibration scheduled
⛔ NEVER skip Step 3 (real API check). Guessing your AI visibility = flying blind.
LLMs (and tired humans) will try to skip steps. Here are pre-written rebuttals:
ExcuseRebuttal"I know my brand ranks on AI search"You don't. 75% of brands that think they're visible on DeepSeek are wrong. The only way to know is to actually query the API."ChatGPT GEO strategies work for DeepSeek too"They don't. DeepSeek cites 知乎/CSDN, ChatGPT cites English blogs. Different sources, different citation logic, different optimization."I'll just optimize for all engines the same way"Each engine has different citation style, preferred sources, and content length. One-size-fits-all = one-size-fits-none."Content prediction is unnecessary, I know what works"You don't. Without prediction + calibration, you're guessing. Guessing = wasted content budget."I'll check visibility after publishing"After publishing = after wasting resources on content that doesn't rank. Check BEFORE with API."My brand is too small for AI engines to notice"Small brands rank on AI search MORE easily than traditional SEO — AI engines cite specific data, not domain authority."I don't need to adapt content per engine"DeepSeek wants 50-150 word data-driven excerpts. Kimi wants 2000+ word deep analysis. Same content can't serve both."Calibration is too much work"Without calibration, your predictions never improve. 5 calibrations = 40% prediction accuracy improvement. The work pays for itself.
bash
cd scripts/
# 查看中国AI引擎深度数据
./cn-ai-engines.sh deepseek
# 预测内容在各AI引擎的表现
./predict.sh "你的内容" --platform xiaohongshu
本Skill包含 真实API后端,提供中国AI引擎的深度数据:
text
https://1341839497-2yuxt6z58d.ap-guangzhou.tencentscf.com
引用风格:内联引用
偏好来源:知乎 > CSDN > 36氪 > 微信公众号 > 行业白皮书
内容偏好:事实+数据型内容,50-150字引用
优化要点:
引用风格:脚注引用
偏好来源:知乎 > 微信公众号 > 长文博客 > 学术论文
内容偏好:深度长文(2000字+),100-300字引用
优化要点:
引用风格:内联引用
偏好来源:抖音 > 今日头条 > 西瓜视频 > 飞书文档
内容偏好:短视频文案+头条号文章,30-80字引用
优化要点:
引用风格:搜索整合
偏好来源:淘宝 > 钉钉文档 > 阿里云开发者社区 > 1688
内容偏好:产品参数+用户评价型内容
优化要点:
引用风格:搜索结果整合
偏好来源:百度百科 > 百度知道 > 百度文库 > 百家号
内容偏好:百科式结构化内容
优化要点:
借鉴科学实验方法论,每次发布内容前先预测,发布后复盘校准:
维度说明评分范围合规风险内容被平台处罚/限流的风险0-100(0=合规)互动潜力内容获得点赞/评论/分享的概率0-100品牌安全内容对品牌形象的影响0-100(0=安全)搜索可见度内容在目标平台被搜索到的概率0-100AI引用概率内容被AI搜索引擎引用的概率0-100
阶段条件预测模式准确度冷启动期0篇复盘数据简化5维打分低学习期1-4篇复盘数据5维打分+bucket预测中校准期5+篇复盘数据完整5组件预测+置信区间高
text
1. 发布前:调用 /predict 获取5维预测评分
2. 记录预测:保存预测结果(不可修改!)
3. 发布内容
4. T+3天:复盘实际数据 vs 预测
5. 校准:根据偏差调整评分权重
6. 重复 → 越用越准
同一内容,针对不同AI引擎调整格式:
引擎内容形态发布平台字数DeepSeek数据分析型知乎/CSDN800-1500Kimi深度长文公众号/博客2000-5000豆包短视频文案抖音/头条200-500通义产品参数型淘宝/1688300-800文心百科结构型百家号/百科500-1500