Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Discover which AI prompts and topics matter for a brand's Answer Engine Optimization (AEO) using only free tools. Crawls a website, analyzes the brand's posi...
Discover which AI prompts and topics matter for a brand's Answer Engine Optimization (AEO) using only free tools. Crawls a website, analyzes the brand's posi...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Source: github.com/psyduckler/aeo-skills Part of: AEO Skills Suite โ Prompt Research โ Content โ Analytics Discover which prompts and topics matter for a brand's AI visibility โ using zero paid APIs.
web_fetch โ crawl the target site web_search โ Brave Search free tier (optional but recommended) LLM reasoning โ the agent's own model does the heavy lifting No API keys, no paid tools, no accounts needed.
The user provides: Domain URL (required) โ e.g. clearscope.io Niche/category (optional) โ e.g. "SEO software for content teams" Competitors (optional) โ e.g. "Surfer SEO, MarketMuse, Frase"
Using the brand understanding, brainstorm topic categories. For methodology and category types, read references/aeo-methodology.md. Core prompt categories to generate: Problem-aware โ "How do I solve [problem]?" Solution-aware โ "What tools exist for [category]?" Comparison โ "[Brand] vs [competitor]" Best-of โ "Best [category] for [use case]" How-to โ "How to [task the product helps with]" Evaluation โ "Is [brand] good for [need]?" Industry โ "[Industry] trends / best practices"
For each category, generate 5-15 specific prompts people would actually ask an AI assistant. Guidelines: Write naturally โ how people talk to ChatGPT, not how they Google Be specific โ include context (company size, industry, use case) Vary intent โ research, comparison, how-to, buying decision Avoid jargon-heavy or unrealistic prompts
Score each prompt (1-5) on: Relevance โ How closely tied to the brand's core offering? Volume potential โ How many people likely ask this? Winability โ Can this brand realistically be the best answer? Intent value โ Does this indicate buying/conversion intent? Formula: Priority = (Relevance ร 2 + Volume + Winability + Intent) / 5 Sort into Tier 1 (โฅ3.5), Tier 2 (2.5-3.4), Tier 3 (<2.5).
For Tier 1 prompts, use web_search with site:domain.com [topic keywords] to check if content already exists. Rate coverage: Strong โ Dedicated page directly answers the prompt Partial โ Related content exists but doesn't fully address it None โ No relevant content found
Output a structured report with: Brand summary (2-3 sentences) Prioritized prompt list with scores and coverage status Content gap analysis (high-priority prompts with no coverage) Top 5 recommended content pieces to create first Use the output format from references/aeo-methodology.md.
If web_search is unavailable, the skill still works โ just skip the coverage audit or have the user manually check For competitor analysis, crawl competitor sites too and compare topic coverage Re-run quarterly โ AI prompt trends shift as models and user behavior evolve The agent's own knowledge of the industry is a valid research input โ use it
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