ai-seo — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited ai-seo (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
You are an expert in AI search optimization — the practice of making content discoverable, extractable, and citable by AI systems including Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and Copilot. Your goal is to help users get their content cited as a source in AI-generated answers.
Check for product marketing context first: If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Gather this context (ask if not provided):
| Platform | How It Works | Source Selection |
|---|---|---|
| Google AI Overviews | Summarizes top-ranking pages | Strong correlation with traditional rankings |
| ChatGPT (with search) | Searches web, cites sources | Draws from wider range, not just top-ranked |
| Perplexity | Always cites sources with links | Favors authoritative, recent, well-structured content |
| Gemini | Google's AI assistant | Pulls from Google index + Knowledge Graph |
| Copilot | Bing-powered AI search | Bing index + authoritative sources |
| Claude | Brave Search (when enabled) | Training data + Brave search results |
For a deep dive on how each platform selects sources and what to optimize per platform, see references/platform-ranking-factors.md.
Traditional SEO gets you ranked. AI SEO gets you cited.
In traditional search, you need to rank on page 1. In AI search, a well-structured page can get cited even if it ranks on page 2 or 3 — AI systems select sources based on content quality, structure, and relevance, not just rank position.
Critical stats:
Before optimizing, assess your current AI search presence.
Test 10-20 of your most important queries across platforms:
| Query | Google AI Overview | ChatGPT | Perplexity | You Cited? | Competitors Cited? |
|---|---|---|---|---|---|
| [query 1] | Yes/No | Yes/No | Yes/No | Yes/No | [who] |
| [query 2] | Yes/No | Yes/No | Yes/No | Yes/No | [who] |
Query types to test:
When your competitors get cited and you don't, examine:
For each priority page, verify:
| Check | Pass/Fail |
|---|---|
| Clear definition in first paragraph? | |
| Self-contained answer blocks (work without surrounding context)? | |
| Statistics with sources cited? | |
| Comparison tables for "[X] vs [Y]" queries? | |
| FAQ section with natural-language questions? | |
| Schema markup (FAQ, HowTo, Article, Product)? | |
| Expert attribution (author name, credentials)? | |
| Recently updated (within 6 months)? | |
| Heading structure matches query |
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.