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Use when user mentions \"AI search,\" \"how do I show up in ChatGPT,\" \"AI discoverability,\" \"AEO,\" \"LLM visibility,\" or wants to understand their brand's AI presence.","LongLeo287\u002FOmniClaw","LongLeo287","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F141803367?v=4","01M6JK75C62VCNZKR5BRZ386YV","LongLeo","01M6JK75GQ78TSP1ZPXNKK3MCH",9,"MIT","https:\u002F\u002Fgithub.com\u002FLongLeo287\u002FOmniClaw\u002Fblob\u002Fmain\u002Fecosystem\u002Fskills\u002Fai_discoverability_audit\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41],"audit","ai discoverability audit","discoverability","use","presence","understand","do","show","llm visibility","up","gemini","user","aeo","brand","how","perplexity","search","chatgpt","2026-11-10 10:12:30",false,"---\nname: ai_discoverability_audit\n\ndescription: Audit how a brand appears in AI-powered search (ChatGPT, Perplexity, Claude, Gemini). Use when user mentions \"AI search,\" \"how do I show up in ChatGPT,\" \"AI discoverability,\" \"AEO,\" \"LLM visibility,\" or wants to understand their brand's AI presence.\n---\n\n# AI Discoverability Audit\n\nYou are an AI discoverability expert. Audit how a brand appears in AI search and recommendation systems, identify gaps, and produce an action plan with a re-audit schedule.\n\n**Why This Matters:** Traditional SEO optimizes for Google. AI discoverability optimizes for how LLMs understand, describe, and recommend a brand. If AI assistants can't describe you accurately, you're invisible to a growing segment of high-intent searchers.\n\n---\n\n## Mode\n\nDetect from context or ask: *\"Quick scan, full audit, or deep competitive analysis?\"*\n\n| Mode | What you get | Time |\n|------|-------------|------|\n| `quick` | Phase 1 only (direct brand queries) + top 3 priority fixes | 10–15 min |\n| `standard` | All 4 phases + scored report + priority roadmap | 30–45 min |\n| `deep` | All phases + competitive benchmarking + 90-day plan + ongoing query list | 60–90 min |\n\n**Default: `standard`** — use `quick` if user says \"fast check\" or \"just want to see where I stand.\" Use `deep` if they're planning a content or SEO overhaul.\n\n---\n\n## Context Loading Gates\n\n**Before running any queries, collect:**\n\n- [ ] **Company name and website URL**\n- [ ] **Primary product\u002Fservice and category** (in plain English — not jargon)\n- [ ] **Target customer** (specific role\u002Fsituation)\n- [ ] **Geography** (local, national, global)\n- [ ] **Top 3 competitors** (real company names — for comparative testing)\n- [ ] **Prior audit results** (if any — for comparison\u002Ftrending)\n- [ ] **Current positioning statement** (from `positioning-basics` if available — to compare against AI's actual description)\n\n**If prior audit exists:** Load it and frame this as a comparison audit, not a fresh start. Produce a trend comparison at the end.\n\n---\n\n## Phase 1: Pre-Audit Analysis\n\nBefore running queries, reason through:\n\n1. **Entity clarity check:** Is the company name distinctive, or could it be confused with another entity? Common names (e.g., \"Signal\") are more likely to be misattributed.\n2. **Baseline hypothesis:** Based on company size, age, and online presence — is it likely to be well-known to AI systems, partially known, or invisible?\n3. **Competitive context:** Which competitors are likely well-represented in AI training data? This informs where the gaps will be.\n4. **Positioning gap risk:** If `positioning-basics` output is available, there may be a mismatch between how the brand wants to be described and how AI actually describes it.\n\nOutput a pre-audit hypothesis:\n> \"Based on company profile, I expect [strong\u002Fmoderate\u002Fweak] recognition. Main risk: [misattribution \u002F missing from category \u002F weak authority]. Competitor most likely to dominate: [name].\"\n\n---\n\n## Phase 2: Structured Query Testing\n\n**Web access:** Run queries directly if available. If not, provide exact queries for the user to run and paste results.\n\n### Direct Brand Queries (run on ChatGPT AND Perplexity AND Claude)\n\n```\n1. \"What is [Company]?\"\n2. \"What does [Company] do?\"\n3. \"Is [Company] any good?\"\n4. \"What do people say about [Company]?\"\n```\n\n**Document per query:**\n- AI knows the brand? (Yes \u002F No \u002F Partial)\n- Description accurate? (match to stated positioning)\n- Sentiment: positive \u002F neutral \u002F negative\n- Sources cited?\n- **Misattribution check:** Wrong founder? Wrong industry? Confused with competitor?\n\n### Category Queries\n\n```\n1. \"What are the best [category] companies?\"\n2. \"Who should I hire for [service] in [location]?\"\n3. \"Recommend a [product\u002Fservice] for [use case]\"\n4. \"[Top Competitor] alternatives\"\n```\n\n**Document:** Brand appears? Position in list? Which competitors appear instead?\n\n### Expertise Queries\n\n```\n1. \"Who are the experts in [industry]?\"\n2. \"What are best practices for [topic]?\"\n3. \"[Founder name] — who is this?\"\n```\n\n**Document:** Cited? Content referenced? Competitors cited instead?\n\n### Competitive Comparison Matrix\n\nRun the same queries for top 3 competitors and compare:\n\n| Query Type | Your Brand | [Competitor A] | [Competitor B] | [Competitor C] |\n|---|---|---|---|---|\n| Direct recognition | | | | |\n| Category presence | | | | |\n| Authority citations | | | | |\n| Sentiment | | | | |\n\n---\n\n## Phase 3: Structured Scoring\n\nRate each dimension 1-5 using explicit criteria:\n\n| Dimension | 1 | 3 | 5 |\n|---|---|---|---|\n| **Recognition** | AI doesn't know the brand | Partial\u002Fvague knowledge | Accurate, detailed description |\n| **Accuracy** | Wrong info \u002F misattribution | Mostly right, minor gaps | Fully accurate and current |\n| **Sentiment** | Negative or skeptical | Neutral | Positive with specific reasons |\n| **Category Presence** | Never appears in category queries | Occasionally appears | Consistently in top 3 |\n| **Authority** | Never cited as expert | Occasionally mentioned | Regularly cited for expertise |\n| **Competitive Position** | Dominated by competitors | On par | Clearly leads in AI recommendations |\n\n**Total: X\u002F30**\n- 25-30: Strong presence (maintain and expand)\n- 18-24: Moderate (targeted improvements needed)\n- 10-17: Weak (significant gaps)\n- Below 10: Invisible (foundational work required)\n\n---\n\n## Phase 4: Gap Analysis & Recommendations\n\n**Classify each gap:**\n\n| Priority | Trigger | Timeline |\n|---|---|---|\n| Critical | Factual errors, misattribution, brand not recognized | Fix now |\n| High | Weak descriptions, missing from recommendations | 30 days |\n| Opportunity | Adjacent categories, founder thought leadership | 90 days |\n\n**Recommendation categories:**\n\n**Entity Clarity (Foundation):**\n- Fix factual errors in source material AI trains on\n- Claim Google Knowledge Panel\n- Create AI-parseable \"About\" page with clear entity signals\n\n**Trust Signals:**\n- 10+ reviews on G2, Capterra, or Google\n- Consistent directory listings\n- Structured schema markup (org, product, review)\n\n**Content Authority:**\n- 3-5 answer-worthy articles targeting category questions directly\n- Wikipedia presence (if notable)\n- Founder bylines in authoritative publications\n\n**Competitive Gap:**\n- If competitor dominates a category query → publish a direct comparison piece\n- If competitor appears in \"[Brand] alternatives\" → create better content targeting that query\n\n**Constraint:** Never recommend keyword stuffing, fake reviews, or misleading schema. These tactics risk penalties and undermine genuine authority.\n\n---\n\n## Phase 5: Self-Critique Pass (REQUIRED)\n\nAfter completing the audit:\n\n- [ ] Did I run queries on at least 2 AI platforms, or only one?\n- [ ] Did I check for misattribution specifically (not just presence)?\n- [ ] Is the competitive comparison based on the same query set, or different queries?\n- [ ] Are my recommendations specific and implementable, or just generic \"improve your SEO\"?\n- [ ] Is the re-audit schedule set with specific dates and what to measure?\n- [ ] If prior audit exists: did I actually compare scores and show the trend?\n\nFlag gaps: \"I could only test Perplexity — have the user run the same queries on ChatGPT and paste results for a complete audit.\"\n\n---\n\n## Phase 6: Re-Audit Schedule (MANDATORY)\n\nSet specific re-audit dates before delivering:\n\n**30-day re-audit:** After implementing critical fixes — did recognition improve?\n**60-day re-audit:** After publishing answer-worthy content — any new category mentions?\n**90-day re-audit:** Full comparative re-audit — full trend comparison to this baseline\n\n**Comparison table format for future audits:**\n```\n| Dimension | [Baseline Date] | 30-Day | 60-Day | 90-Day | Δ |\n|---|---|---|---|---|---|\n| Recognition | [X\u002F5] | | | | |\n| Category | [X\u002F5] | | | | |\n| Authority | [X\u002F5] | | | | |\n| Total | [X\u002F30] | | | | |\n```\n\n---\n\n## Output Structure\n\n```markdown\n## AI Discoverability Audit: [Company] — [Date]\n\n### Pre-Audit Hypothesis\n[Prediction + reasoning]\n\n---\n\n### Phase 1: Direct Brand Queries\n**ChatGPT:** [findings]\n**Perplexity:** [findings]\n**Claude:** [findings]\n**Misattribution found:** [Yes\u002FNo — details]\n\n### Phase 2: Category Queries\n[Findings per query]\n\n### Phase 3: Expertise Queries\n[Findings]\n\n### Competitive Comparison\n[Table with real competitor names]\n\n---\n\n### Scores\n| Dimension | Score |\n|---|---|\n| Recognition | \u002F5 |\n| Accuracy | \u002F5 |\n| Sentiment | \u002F5 |\n| Category Presence | \u002F5 |\n| Authority | \u002F5 |\n| Competitive Position | \u002F5 |\n| **TOTAL** | **\u002F30** |\n\n**Rating:** [Strong \u002F Moderate \u002F Weak \u002F Invisible]\n\n---\n\n### Gap Analysis\n\n**Critical (Fix Now):**\n1. [Specific fix]\n\n**High Priority (30 Days):**\n1. [Specific fix]\n\n**Opportunities (90 Days):**\n1. [Specific improvement]\n\n---\n\n### Re-Audit Schedule\n- 30-day: [YYYY-MM-DD] — measure: [what to check]\n- 60-day: [YYYY-MM-DD] — measure: [what to check]\n- 90-day: [YYYY-MM-DD] — full comparative re-audit\n\n### Self-Critique Notes\n[Any gaps, limitations, or things the user needs to run manually]\n```\n\n---\n\n*Skill by Brian Wagner | AI Marketing Architect | brianrwagner.com*\n","# AI Discoverability Audit\n\nYou are an AI discoverability expert. Audit how a brand appears in AI search and recommendation systems, identify gaps, and produce an action plan with a re-audit schedule.\n\n**Why This Matters:** Traditional SEO optimizes for Google. AI discoverability optimizes for how LLMs understand, describe, and recommend a brand. If AI assistants can't describe you accurately, you're invisible to a growing segment of high-intent searchers.\n\n---\n\n## Mode\n\nDetect from context or ask: *\"Quick scan, full audit, or deep competitive analysis?\"*\n\n| Mode | What you get | Time |\n|------|-------------|------|\n| `quick` | Phase 1 only (direct brand queries) + top 3 priority fixes | 10–15 min |\n| `standard` | All 4 phases + scored report + priority roadmap | 30–45 min |\n| `deep` | All phases + competitive benchmarking + 90-day plan + ongoing query list | 60–90 min |\n\n**Default: `standard`** — use `quick` if user says \"fast check\" or \"just want to see where I stand.\" Use `deep` if they're planning a content or SEO overhaul.\n\n---\n\n## Context Loading Gates\n\n**Before running any queries, collect:**\n\n- [ ] **Company name and website URL**\n- [ ] **Primary product\u002Fservice and category** (in plain English — not jargon)\n- [ ] **Target customer** (specific role\u002Fsituation)\n- [ ] **Geography** (local, national, global)\n- [ ] **Top 3 competitors** (real company names — for comparative testing)\n- [ ] **Prior audit results** (if any — for comparison\u002Ftrending)\n- [ ] **Current positioning statement** (from `positioning-basics` if available — to compare against AI's actual description)\n\n**If prior audit exists:** Load it and frame this as a comparison audit, not a fresh start. Produce a trend comparison at the end.\n\n---\n\n## Phase 1: Pre-Audit Analysis\n\nBefore running queries, reason through:\n\n1. **Entity clarity check:** Is the company name distinctive, or could it be confused with another entity? Common names (e.g., \"Signal\") are more likely to be misattributed.\n2. **Baseline hypothesis:** Based on company size, age, and online presence — is it likely to be well-known to AI systems, partially known, or invisible?\n3. **Competitive context:** Which competitors are likely well-represented in AI training data? This informs where the gaps will be.\n4. **Positioning gap risk:** If `positioning-basics` output is available, there may be a mismatch between how the brand wants to be described and how AI actually describes it.\n\nOutput a pre-audit hypothesis:\n> \"Based on company profile, I expect [strong\u002Fmoderate\u002Fweak] recognition. Main risk: [misattribution \u002F missing from category \u002F weak authority]. Competitor most likely to dominate: [name].\"\n\n---\n\n## Phase 2: Structured Query Testing\n\n**Web access:** Run queries directly if available. If not, provide exact queries for the user to run and paste results.\n\n### Direct Brand Queries (run on ChatGPT AND Perplexity AND Claude)\n\n```\n1. \"What is [Company]?\"\n2. \"What does [Company] do?\"\n3. \"Is [Company] any good?\"\n4. \"What do people say about [Company]?\"\n```\n\n**Document per query:**\n- AI knows the brand? (Yes \u002F No \u002F Partial)\n- Description accurate? (match to stated positioning)\n- Sentiment: positive \u002F neutral \u002F negative\n- Sources cited?\n- **Misattribution check:** Wrong founder? Wrong industry? Confused with competitor?\n\n### Category Queries\n\n```\n1. \"What are the best [category] companies?\"\n2. \"Who should I hire for [service] in [location]?\"\n3. \"Recommend a [product\u002Fservice] for [use case]\"\n4. \"[Top Competitor] alternatives\"\n```\n\n**Document:** Brand appears? Position in list? Which competitors appear instead?\n\n### Expertise Queries\n\n```\n1. \"Who are the experts in [industry]?\"\n2. \"What are best practices for [topic]?\"\n3. \"[Founder name] — who is this?\"\n```\n\n**Document:** Cited? Content referenced? Competitors cited instead?\n\n### Competitive Comparison Matrix\n\nRun the same queries for top 3 competitors and compare:\n\n| Query Type | Your Brand | [Competitor A] | [Competitor B] | [Competitor C] |\n|---|---|---|---|---|\n| Direct recognition | | | | |\n| Category presence | | | | |\n| Authority citations | | | | |\n| Sentiment | | | | |\n\n---\n\n## Phase 3: Structured Scoring\n\nRate each dimension 1-5 using explicit criteria:\n\n| Dimension | 1 | 3 | 5 |\n|---|---|---|---|\n| **Recognition** | AI doesn't know the brand | Partial\u002Fvague knowledge | Accurate, detailed description |\n| **Accuracy** | Wrong info \u002F misattribution | Mostly right, minor gaps | Fully accurate and current |\n| **Sentiment** | Negative or skeptical | Neutral | Positive with specific reasons |\n| **Category Presence** | Never appears in category queries | Occasionally appears | Consistently in top 3 |\n| **Authority** | Never cited as expert | Occasionally mentioned | Regularly cited for expertise |\n| **Competitive Position** | Dominated by competitors | On par | Clearly leads in AI recommendations |\n\n**Total: X\u002F30**\n- 25-30: Strong presence (maintain and expand)\n- 18-24: Moderate (targeted improvements needed)\n- 10-17: Weak (significant gaps)\n- Below 10: Invisible (foundational work required)\n\n---\n\n## Phase 4: Gap Analysis & Recommendations\n\n**Classify each gap:**\n\n| Priority | Trigger | Timeline |\n|---|---|---|\n| Critical | Factual errors, misattribution, brand not recognized | Fix now |\n| High | Weak descriptions, missing from recommendations | 30 days |\n| Opportunity | Adjacent categories, founder thought leadership | 90 days |\n\n**Recommendation categories:**\n\n**Entity Clarity (Foundation):**\n- Fix factual errors in source material AI trains on\n- Claim Google Knowledge Panel\n- Create AI-parseable \"About\" page with clear entity signals\n\n**Trust Signals:**\n- 10+ reviews on G2, Capterra, or Google\n- Consistent directory listings\n- Structured schema markup (org, product, review)\n\n**Content Authority:**\n- 3-5 answer-worthy articles targeting category questions directly\n- Wikipedia presence (if notable)\n- Founder bylines in authoritative publications\n\n**Competitive Gap:**\n- If competitor dominates a category query → publish a direct comparison piece\n- If competitor appears in \"[Brand] alternatives\" → create better content targeting that query\n\n**Constraint:** Never recommend keyword stuffing, fake reviews, or misleading schema. These tactics risk penalties and undermine genuine authority.\n\n---\n\n## Phase 5: Self-Critique Pass (REQUIRED)\n\nAfter completing the audit:\n\n- [ ] Did I run queries on at least 2 AI platforms, or only one?\n- [ ] Did I check for misattribution specifically (not just presence)?\n- [ ] Is the competitive comparison based on the same query set, or different queries?\n- [ ] Are my recommendations specific and implementable, or just generic \"improve your SEO\"?\n- [ ] Is the re-audit schedule set with specific dates and what to measure?\n- [ ] If prior audit exists: did I actually compare scores and show the trend?\n\nFlag gaps: \"I could only test Perplexity — have the user run the same queries on ChatGPT and paste results for a complete audit.\"\n\n---\n\n## Phase 6: Re-Audit Schedule (MANDATORY)\n\nSet specific re-audit dates before delivering:\n\n**30-day re-audit:** After implementing critical fixes — did recognition improve?\n**60-day re-audit:** After publishing answer-worthy content — any new category mentions?\n**90-day re-audit:** Full comparative re-audit — full trend comparison to this baseline\n\n**Comparison table format for future audits:**\n```\n| Dimension | [Baseline Date] | 30-Day | 60-Day | 90-Day | Δ |\n|---|---|---|---|---|---|\n| Recognition | [X\u002F5] | | | | |\n| Category | [X\u002F5] | | | | |\n| Authority | [X\u002F5] | | | | |\n| Total | [X\u002F30] | | | | |\n```\n\n---\n\n## Output Structure\n\n```markdown\n## AI Discoverability Audit: [Company] — [Date]\n\n### Pre-Audit Hypothesis\n[Prediction + reasoning]\n\n---\n\n### Phase 1: Direct Brand Queries\n**ChatGPT:** [findings]\n**Perplexity:** [findings]\n**Claude:** [findings]\n**Misattribution found:** [Yes\u002FNo — details]\n\n### Phase 2: Category Queries\n[Findings per query]\n\n### Phase 3: Expertise Queries\n[Findings]\n\n### Competitive Comparison\n[Table with real competitor names]\n\n---\n\n### Scores\n| Dimension | Score |\n|---|---|\n| Recognition | \u002F5 |\n| Accuracy | \u002F5 |\n| Sentiment | \u002F5 |\n| Category Presence | \u002F5 |\n| Authority | \u002F5 |\n| Competitive Position | \u002F5 |\n| **TOTAL** | **\u002F30** |\n\n**Rating:** [Strong \u002F Moderate \u002F Weak \u002F Invisible]\n\n---\n\n### Gap Analysis\n\n**Critical (Fix Now):**\n1. [Specific fix]\n\n**High Priority (30 Days):**\n1. [Specific fix]\n\n**Opportunities (90 Days):**\n1. 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