local-visibility-skill_skill

This skill delivers data-driven local visibility and AI-search insights from Local Falcon, guiding GPB optimization and strategic actions for multi-location
  • Python

2.5k

GitHub Stars

7

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill openclaw/skills --skill local-visibility-skill

  • _meta.json296 B
  • AGENTS.md4.1 KB
  • local-falcon-ai-logo.svg8.4 KB
  • marketplace.json3.6 KB
  • package.json979 B
  • README.md5.8 KB
  • SKILL.md22.6 KB

Overview

This skill delivers expert guidance on AI Visibility and Local SEO based on Local Falcon’s geo-grid rank tracking methodology. It helps agencies, enterprises, and SMBs translate visibility metrics into prioritized actions that drive leads, calls, and foot traffic. The guidance covers AI platforms (ChatGPT, Gemini, Google AI Mode/Overviews, Grok) plus Google Business Profile and local pack tactics.

How this skill works

I assess whether Local Falcon MCP tools are connected and state the operating mode: ORCHESTRATION (live data access) or GUIDANCE (strategy and setup help). In orchestration mode I can pull scans, reports, and place IDs to deliver data-driven diagnostics; in guidance mode I provide proven frameworks, checklists, and setup steps for MCP connection. Recommendations map metrics (SoLV, SAIV, ATRP/ARP) to concrete actions across short, medium, and long horizons.

When to use it

  • You want to improve map pack rankings or diagnose local pack drops (SoLV issues).
  • You need to appear in AI-driven results (SAIV) like AI Overviews, AI Mode, Gemini, ChatGPT, or Grok.
  • You manage multi-location or franchise SEO and need scalable diagnostics.
  • You want help connecting Local Falcon MCP for live scans and automated analysis.
  • You’re auditing review strategy, citations, or GBP configuration for performance gaps.

Best practices

  • Always state assumptions upfront and confirm center points for Service Area Businesses.
  • Prioritize fixes: immediate (GBP errors, center point), medium (reviews, citations), long (AI content & PR).
  • Treat SoLV (maps) and SAIV (AI) as separate KPIs with different data sources and actions.
  • Use third-party citations and editorial mentions to boost AI visibility; optimize GBP for map pack.
  • If MCP is available, run geo-grid scans with AI analysis enabled before prescribing changes.

Example use cases

  • Diagnose a sudden SoLV drop near your storefront and get a prioritized remediation plan.
  • Map an AI visibility (SAIV) gap for a regional brand and create a citation + editorial outreach plan.
  • Set up Local Falcon MCP for a franchise roll‑out to automate scans and competitive tracking.
  • Audit GBP and review signals to translate a review deficit into a conversion-focused campaign.
  • Compare competitor footprint across a geo-grid to find low-competition expansion corridors.

FAQ

I will tell you explicitly which mode I’m in: ORCHESTRATION if MCP tools are connected, or GUIDANCE if they are not. If not connected, I’ll provide MCP setup steps.

What’s the difference between SoLV and SAIV?

SoLV measures map pack dominance (top-3 placements on Google/Apple Maps). SAIV measures mentions in AI responses (ChatGPT, Gemini, AI Mode, Grok). They require different fixes and data sources.

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