AgentStack
SKILL verified MIT Self-run

Seo Ai Search Share Of Voice

skill-amirjahfar1-automate-seo-with-claude-seo-ai-search-share-of-voice · by amirjahfar1

Measure AI Search share of voice for a target domain versus competitors across ChatGPT, Perplexity, Gemini, Google AI Overview, and AI Mode. Pulls the AIO leaderboard, then samples prompts where each domain appears as a source or brand mention, and analyses topic clusters each brand owns. Use when the user asks for AI Search share of voice, LLM visibility tracking, AEO/GEO analysis, AI Overview c…

No reviews yet
0 installs
2 views
0.0% view→install

Install

$ agentstack add skill-amirjahfar1-automate-seo-with-claude-seo-ai-search-share-of-voice

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

Are you the author of Seo Ai Search Share Of Voice? Claim this listing to set pricing, connect Stripe payouts, and keep 70% of every sale.
Sign up to claim

About

> Example output: [examples/seo-ai-search-share-of-voice-wix-com-20260427/REPORT.md](../../examples/seo-ai-search-share-of-voice-wix-com-20260427/REPORT.md)

AI Search Share of Voice

Compare AI-search visibility for a target brand against competitors across every major LLM engine, then analyse the topic clusters each brand owns and where gaps exist.

Prerequisites

  • DataForSEO MCP server connected.
  • User provides: (a) target domain and its brand name, (b) list of competitor domains and brand names, (c) country (default: us), and (d) optionally, which engines to analyse (default: all supported: ai-overview, chatgpt, perplexity, gemini, ai-mode).

Process

  1. Leaderboard snapshot mcp__dataforseo__ai_opt_llm_ment_top_domains + mcp__dataforseo__ai_opt_llm_ment_agg_metrics; Google AI Overview presence from mcp__dataforseo__serp_organic_live_advanced (AIO block)
  • Pull the LLM-mention leaderboard (top cited/mentioned domains) for the target domain's category in the target country; for the AI Overview engine, read the AIO citation block from serp_organic_live_advanced on the category's seed keywords.
  • Capture mention counts and share percentages per engine, per domain.
  1. Heatmap table
  • Build a table: rows = domains (target + competitors), columns = engines, cells = % share of voice.
  • Highlight the leader per engine and the worst performer.
  1. Prompt sampling per domain mcp__dataforseo__ai_opt_llm_ment_search, mcp__dataforseo__ai_opt_llm_ment_top_pages; for actual answers mcp__dataforseo__ai_optimization_chat_gpt_scraper / mcp__dataforseo__ai_optimization_llm_response
  • For each domain (target and each competitor):
  • Use ai_opt_llm_ment_search to pull prompts/queries where the domain appears as a cited source (link mention) and where the brand is mentioned by name; ai_opt_llm_ment_top_pages surfaces the specific pages cited.
  • Where a live answer is needed to confirm a mention, scrape it with ai_optimization_chat_gpt_scraper (ChatGPT) or ai_optimization_llm_response (other models).
  • Save query text and the exact sources cited so the user can validate.
  1. Topic clustering
  • Group prompts by theme (e.g., pricing, feature comparison, tutorials, alternatives, reviews).
  • For each brand, note which clusters it dominates and which it is absent from.
  1. Gap and recommendation synthesis
  • Identify 3 to 5 topic clusters where the target underperforms competitors despite having relevant content.
  • Recommend specific actions: new content angles, structured data additions, partnerships with frequently-cited sources, comparison pages, FAQ/How-To schema.

Output format

Create a folder seo-ai-search-share-of-voice-{target-slug}-{YYYYMMDD}/ with:

seo-ai-search-share-of-voice-{target-slug}-{YYYYMMDD}/
├── 01-leaderboard.md         # raw leaderboard per engine
├── 02-heatmap.md             # visual heatmap table
├── 03-prompts-{domain}.md    # one file per domain with 20 sampled prompts
├── 04-topic-clusters.md      # cluster membership per brand
└── REPORT.md                 # executive summary

REPORT.md follows this shape:

# AI Search Share of Voice: {target brand} vs competitors

## Summary
- Target: {target} ({share}% across all engines)
- Leader: {leader brand} ({share}%)
- Target rank: {n} of {total}

## Heatmap

| Domain | AI Overview | ChatGPT | Perplexity | Gemini | AI Mode |
|---|---|---|---|---|---|
| {target} | {%} | {%} | {%} | {%} | {%} |
| {comp1} | ... | ... | ... | ... | ... |

## Who owns what

### {target brand}
Strong in: {cluster 1}, {cluster 2}
Absent from: {cluster 3}, {cluster 4}

### {competitor 1 brand}
...

## Topic cluster ownership

| Cluster | Leader | Share | Target position | Gap |
|---|---|---|---|---|
| Pricing | {brand} | {%} | {n} | {% behind} |
| Alternatives | {brand} | {%} | {n} | {% behind} |
| Tutorials | {brand} | {%} | {n} | {% behind} |

## Top 5 actions to close gaps
1. {action with target cluster}
2. ...

Tips

  • Do not hallucinate citation counts. If the API returns zero prompts for a given domain/engine, report zero, do not estimate.
  • For each competitor, validate the brand-name match in the prompt text. Sometimes "Wix" appears in a sentence about "wiktionary" or a person's name. Flag ambiguous matches in the raw-prompt file.
  • base_domain scope is the default; do not narrow to subdomain unless the user asks.
  • DataForSEO allows up to 2,000 calls/min, 30 concurrent; pace sequentially. With 5 domains and 2 mention queries per engine per domain, pace the loop. DataForSEO bills per call — cap large mention lists with limit and ai_optimization_llm_mentions_filters.
  • The report is not a one-time artefact. Recommend the user re-run monthly and diff results to see ranking momentum.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

No reviews yet — be the first.

Versions

  • v0.1.0 Imported from the upstream source.