Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add T4wroot/agentic-seo --skill featured-snippetgit clone --depth 1 https://github.com/T4wroot/agentic-seoWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/t4wroot/agentic-seo/featured-snippet)<a href="https://agentmods.dev/skills/t4wroot/agentic-seo/featured-snippet"><img src="https://agentmods.dev/badge/skills/t4wroot/agentic-seo/featured-snippet/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/t4wroot/agentic-seo/featured-snippet"><img src="https://agentmods.dev/badge/skills/t4wroot/agentic-seo/featured-snippet.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00097 | $0.02202 |
| Opus 5 | $0.00048 | $0.01101 |
| Sonnet 5 | $0.00019 | $0.00440 |
| Haiku 4.5 | $0.00010 | $0.00220 |
Grade A, and why
featured-snippet scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to featured-snippet — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SEO On-Page: Featured Snippet
Guides optimization for Featured Snippets (Position Zero)—direct answers displayed above organic results. Featured snippets appear on ~19% of queries; by 2025, AI Overviews replaced many, but snippet optimization still supports AI citation and PAA. See serp-features for full SERP context.
When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.
Scope
- Featured Snippet formats: Paragraph, list, table
- Content structure: Answer-first, H2/H3, semantic HTML
- Query targeting: How, what, why; positions 2–5 opportunity
- AI Overviews: Layered content for both snippets and AI citation
Current Landscape (2025–2026)
- Featured snippets appear on ~19% of search queries
- AI Overviews replaced 83%+ of featured snippets in many regions; appear in ~47% of US searches
- When AI Overviews show, 83% of searches may end without clicks (zero-click)—goal shifts to citation as well as CTR. Featured Snippets also cause zero-click when the answer suffices. See serp-features for zero-click by feature.
- Position zero still captures ~35% of clicks when snippets appear; pages with snippets see ~8% higher organic CTR
- Optimize for both traditional snippets and AI Overviews
Featured Snippet vs AI Overview
Not the same. Featured snippets pull a direct passage from a single webpage. AI Overviews generate multi-source summaries using AI. When both appear, featured snippets still occupy a highly visible spot. Not every query triggers AI Overview—snippet optimization remains valuable. Semrush
Snippet Formats & Share
| Format | Share | Use | Optimization |
|---|---|---|---|
| Paragraph | ~70% | Definition, "what is," "why" | 40–60 words; direct answer after H2 |
| List | ~19% | How-to, steps, options | <ol> or <ul>; semantic HTML |
| Table | ~6% | Comparisons, stats, specs | Clear headers; target keywords in column/row headers |
| Video | Rare | Visual how-to | Video schema; timestamps/chapters; see video-optimization |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 134 lines · 97 tokens per session scan A d10d83e4a9b8
featured-snippet is a skill published in the GitHub repository T4wroot/agentic-seo (15 stars, last pushed 7d ago), licensed MIT. It adds 97 tokens to every session and 2,202 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to featured-snippet, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
fire-your-seo-agency
A procedure for improving how a website appears in search engines and how AI answer systems find and cite it. It covers search, answer-engine, generative-AI, and Naver visibility.
content-thicken
Evidence-driven blog driver. Takes ONE target from the fused search plus AI-answer content library, pulls the real questions it has to answer, drafts a thick long-form guide against a template contract, validates it deterministically, and stops at preview. Two modes, thicken an already-earning post IN PLACE (never…
backlink-outreach
Find, evaluate, pitch and track natural backlink and content partnerships. Prospects come from the GEO citation data rather than a generic blog search: the targets are the pages an AI already cites when answering your category questions. Research runs on the Monid tool layer (web search and scrape, authority metrics…
geo-monitor
Run and read the GEO pipeline, which measures whether AI answer engines mention, recommend and cite your site. Puts a fixed registry of real user questions to an answer engine through the Monid tool layer, detects the three signals plus competitors, and turns "a rival is named and we are not" into a tracked work…
seo-intake
Run and read the SEO intake pipeline. Pulls the organic keyword set for your domain and for each competitor through the Monid tool layer, computes the gap locally, and routes every keyword to the one action that can help it (write-new / striking / build-depth / defend / noise). Use when asked to refresh the SEO queue…
bing-duplicate-content-fix
Audit article groups, WordPress categories, or supplied URLs for copied content, near-duplicate templates, search-intent overlap, and keyword cannibalization; prepare exact SEO/AEO/GEO fixes; apply only approved WordPress changes; verify saved and public results; and request a Bing recrawl when authorized. Use for…