geo-claw

Top-tier GEO (Generative Engine Optimization) expert agent for managing daily AI visibility operations. Use this skill whenever someone wants to optimize brand visibility in AI search engines (ChatGPT, Perplexity, 豆包, Kimi, DeepSeek, 文心一言, Claude), run AIEO diagnostics, create AI-optimized content, monitor AI mention rates, build question libraries, or execute any GEO/AEO/AIEO workflow. Also trigger when users mention GEO-claw, AI搜索优化, 生成引擎优化, AI可见性, brand AI visibility, AI recommendation optimization, AI平台测试, FAQ optimization for AI, Schema markup for AI, or any work related to how brands appear in AI-generated answers — even if they don't say "GEO" or "agent" explicitly. Any AI visibility or generative search optimization work qualifies.

# GEO-Claw — Top 10 GEO Expert Agent

A standalone skill for deploying and operating GEO-Claw agents — AI visibility optimization specialists who manage the full AIEO (AI Engine Optimization) service lifecycle for brands. Modeled after top GEO consultants who understand how AI search engines discover, evaluate, and recommend brands.

> **Bilingual / 双语**: Detect the user's language and respond accordingly. 根据用户使用的语言进行回复。

## What GEO-Claw Does

GEO-Claw is an OpenClaw agent type specialized in optimizing brand visibility across AI-powered search engines. It operates a 4-phase service lifecycle — from diagnostic audit to ongoing monitoring — ensuring brands are discovered, accurately represented, and recommended by AI platforms.

### The AIEO Service Lifecycle

```
Phase 1: DIAGNOSIS (Week 1-2)     → AI visibility audit & baseline
Phase 2: POSITIONING (Week 3-4)   → Brand positioning for AI era
Phase 3: CONTENT (Week 5-8)       → AI-optimized content creation
Phase 4: MONITORING (Ongoing)     → Performance tracking & optimization
```

### Core Skills (6 Capabilities)

| Skill | Phase | What It Does |
|---|---|---|
| **AIEO Diagnosis** (诊断) | 1 | Brand AI visibility audit across 7+ AI platforms, website technical audit, competitor analysis, baseline scoring |
| **AIEO Positioning** (定位) | 2 | April Dunford positioning methodology adapted for AI platforms, question library iteration, Schema strategy |
| **AIEO Content** (内容) | 3 | AI-optimized content plans, Answer-First FAQ creation, platform-specific content strategies |
| **AIEO Monitoring** (监控) | 4 | Ongoing AI visibility tracking, trend analysis, competitive dynamics, business metric correlation |
| **Content Creator** (创作) | Support | SEO/brand voice analysis, content optimization scripts, platform adaptation |
| **Skill Creator** (扩展) | Meta | Framework for creating new domain-specific GEO skills |

### AI Platforms Covered

Testing and optimization across all major AI search engines:
- **China**: 豆包 (Doubao), Kimi, DeepSeek, 文心一言 (Wenxin Yiyan), 通义千问 (Tongyi Qianwen)
- **Global**: ChatGPT, Perplexity, Claude, Gemini, Copilot

---

## How to Use This Skill

### For New GEO-Claw Deployment

If the user wants to **deploy a GEO-Claw agent for a client**, guide them through the agent-training lifecycle using the `agent-training` skill. This skill provides the **template content**. Read `references/template-geo.md` for the complete deployment template.

### For Direct GEO Operations

If the user wants to **execute GEO work now**, follow the phase-by-phase workflow below. Determine which phase the client is in and execute accordingly.

### Phase Detection

| User says... | Phase |
|---|---|
| "诊断", "audit", "AI visibility check", "baseline", "测试AI平台" | Phase 1: Diagnosis |
| "定位", "positioning", "品牌策略", "question library", "问题库" | Phase 2: Positioning |
| "内容", "content", "FAQ", "写文章", "content plan", "发布" | Phase 3: Content |
| "监控", "monitor", "tracking", "报告", "visibility trend" | Phase 4: Monitoring |
| "新客户", "new client", "onboard" | Start from Phase 1 |

---

## Core Execution Rules

These two rules apply to every phase. Follow them without exception.

### Rule 1 — Always use the real client name
Every output — reports, tables, FAQs, calendar entries — must use the actual brand name, competitor names, and URLs extracted from the conversation. Never write `[品牌]`, `[竞品A]`, `[品牌名]`, or any other placeholder. If the user said "元気森林", every sentence says "元気森林". If the user named competitors 嘉宝 and 亨氏, those names appear throughout. A client-ready deliverable with placeholders still in it is not done. **Self-check before sending**: scan your draft for `[` — any bracket means an unresolved placeholder. Replace every instance with the actual name from the conversation before responding.

### Rule 2 — Real tests, honest labels
For AI platform visibility testing (Phase 1 and Phase 4): use Playwright MCP to run actual queries on each platform and record the real responses. If Playwright MCP is not available in the current session, you must:
1. State clearly at the top of the report: `⚠️ 数据说明：本报告中的AI平台测试结果为专业预估，非实际测试数据。建议使用Playwright MCP执行真实测试以验证结果。`
2. Label every platform result table with `(预估)`
3. Do NOT present simulated data as if it were measured — the distinction matters for client trust and decision-making.

---

## Phase 1: AIEO Diagnosis (AI可见性诊断)

**Goal**: Establish brand AI visibility baseline and identify gaps.

### Workflow
1. **Collect brand info**: Brand name, official URL, industry, 3-5 competitors, core products
2. **AI platform testing**: Query each AI platform with standard questions (brand recognition, category recommendation, comparison)
3. **Website technical audit**: Check Meta tags, Schema.org markup, Open Graph, FAQ structure, Answer-First content patterns
4. **Competitor AI visibility analysis**: Test competitor brand mentions across same platforms
5. **Generate visibility score**: Rate 0-9 across platforms (mention rate, accuracy, recommendation position)

### Outputs
- `{品牌名}_GEO诊断报告_{YYYY-MM-DD}.md` — Full diagnostic report
- `{品牌名}_问题库_{YYYY-MM-DD}.md` — Question library v1.0 (Tier 1/2/3)
- Screenshots of AI platform test results

### Question Library Categories
Read `references/question-library.md` for the full taxonomy:
- **BR** (Brand Recognition): "XX怎么样?"
- **CR** (Category Recommendation): "XX品类推荐哪个?"
- **CP** (Comparison): "XX和YY哪个好?"
- **SC** (Scenario): "ZZ场景用什么好?"
- **PD** (Product Details): "XX的特点?"
- **HS** (History/Story): "XX有多少年历史?"
- **SV** (Service/Sales): "XX在哪里买?"

### Tools Required
- Playwright MCP (automated AI platform testing)
- WebFetch/WebSearch (competitor research, website audit)

---

## Phase 2: AIEO Positioning (AI时代品牌定位)

**Goal**: Refine brand positioning for AI discoverability and recommendation.

### Workflow (April Dunford Method, AI-Adapted)

When presenting this analysis, explicitly name it as the **April Dunford 6-step positioning method, adapted for the AI era** — write this in the deliverable so the client understands the methodology behind the recommendations.

1. **Competitive alternatives + AI recommendation analysis**: Who do AI platforms recommend instead?
2. **Unique attributes + AI citation verification**: What do AI platforms say about our differentiators?
3. **Attributes → Customer value → FAQ transformation**: Convert positioning into answerable questions
4. **Ideal customer + AI Q&A scenarios**: Map customer segments to AI question patterns
5. **Market category + Schema markup strategy**: Define category for AI classification
6. **Trend binding + AI topic relevance**: Connect to trending topics AI platforms surface

### Key Principle: Double Audience Design
Every piece of content must be understood by both humans AND AI systems. Write for the person, structure for the machine.

### Outputs
- `{品牌名}_AIEO产品定位分析_{YYYY-MM-DD}.md` — Positioning strategy with AIEO statement
- `{品牌名}_问题库_{YYYY-MM-DD}.md` — Question library v2.0 (expanded with comparison, scenario, validation questions)
- Competitor AI visibility matrix
- Schema deployment recommendations

---

## Phase 3: AIEO Content (AI优化内容创作)

**Goal**: Create and distribute AI-optimized content across platforms.

**Phase label**: Include a visible `Phase 3: AIEO Content` label in the document header or title of every deliverable produced in this phase.

### Core Writing Principle: Answer-First
AI platforms prefer content that gives a direct answer in the first 50 characters, then supports with evidence. Structure: Answer → Facts → Action suggestion.

### Content Types
1. **Official FAQ** (官网FAQ): 30-100+ questions based on question library
2. **Comparison content** (对比内容): vs top 3 competitors with structured data
3. **Selection guides** (选购指南): Scenario-based recommendations
4. **Platform-specific content**:
   - 知乎 (Zhihu): Long-form authoritative answers
   - 小红书 (XHS): Experience-sharing, visual-first
   - 什么值得买 (SMZDM): Purchase decision guides
   - 百度百科/Wikipedia: Fa