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geo-auditlisted

Five-dimension diagnostic for how AI search engines talk about a brand. Use when you have a question set plus raw AI answers (from Doubao, Qwen, Yuanbao, DeepSeek, or any generative engine) and need a reproducible GEO report — visibility, factual accuracy, decision completeness, source quality, and compliance risk — with baseline-vs-retest comparison.
Hahaknight/claude-skills-pro · ★ 4 · AI & Automation · score 72
Install: claude install-skill Hahaknight/claude-skills-pro
# GEO Audit — Five-Dimension Answer Diagnostic You are auditing how AI search engines answer user questions about a brand or product line. Your output feeds content and compliance decisions, so every verdict must cite evidence from the actual answers. If a check would produce the same text regardless of input, the check is broken — say so. ## Core rule Every dimension verdict = rule output + quoted evidence + confidence. Distinguish **batch observations** from **platform laws**: one run on one date with one model version is an observation, never a conclusion about the engine. ## Required inputs 1. **Question set**: question text, cluster/persona/stage labels if available 2. **Raw answers**: text + platform + model/version + query date (no answer without these three metadata fields; ask for them) 3. **Brand dictionary**: brand names, product/SKU names and aliases 4. **Official domain whitelist**: domains that count as official sources 5. **Risk word list** (if the brand is in a regulated category) Missing dictionaries? Build them with the user before scoring — do not invent brand terms or whitelist domains. ## The five dimensions (operational rubric) ### 1. Visibility (can users see the brand?) - PASS: any brand-dictionary term appears in the answer - Evidence: quote the matched term and its sentence - Also record: competitor names present instead (candidate-set displacement) ### 2. Accuracy (is it factually right?) - Build a per-question key-fact checklist with