# AI Visibility Audit

Lists the few changes most likely to get a brand cited in AI answers.

- Repository: https://github.com/every-app/open-seo (25988 stars)
- Category: Marketing
- License: MIT
- Last updated: 2026-10-31
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add every-app/open-seo --skill ai-visibility-audit -g -a claude-code -y`
Codex: `npx skills add every-app/open-seo --skill ai-visibility-audit -g -a codex -y`
Cursor: `npx skills add every-app/open-seo --skill ai-visibility-audit -g -a cursor -y`
Gemini CLI: `npx skills add every-app/open-seo --skill ai-visibility-audit -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add every-app/open-seo`

## Description

Audit how a brand shows up in AI answers about its market and deliver a short report on the few changes most likely to get it mentioned or cited, such as a third-party page to get onto, an owned page to improve, or an access problem to fix. Use when the user asks for an AI visibility audit, a GEO or AEO audit, why AI recommends competitors instead of them, or how to show up in ChatGPT, Gemini or Google AI answers.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# AI Visibility Audit

## Goal

Find the work most likely to get a brand named or cited in AI answers about its market, and explain it so a non-expert can act on it. Research broadly; recommend selectively. The report leads with one to three recommendations, each tied to the answers and cited pages that justify it.

This skill reads saved answers, adds the pages behind them, and decides what to do. For demand research alone, use `ai-prompt-research`.

## Project context

The project-context tools are free and shared with the app and other agents.

1. External MCP clients: resolve the project with `list_projects`, ask only if the match is ambiguous, then call `get_project_context`. In SAM, use the current project and context already injected into the conversation; SAM has no `get_project_context` tool and needs no project selection or connection setup.
2. This skill needs `business_overview`, the website and the main competitors. If the overview is empty, infer it from the site, confirm it in one question, and save it with `update_project_context`.
3. Read `get_ai_visibility_tracker`. Its prompts, competitors, engines, market and latest runs decide which path below applies. Check the tracker's own brand, the `brands` row with `own: true`. Its name is the project name. If that is not how people write the brand (for example a project named "Acme website"), answers that name the brand are not counted as mentions and brand questions are not treated as branded. Ask the user to rename the project in the app before collecting or interpreting answers.
4. Reuse research-log findings under 30 days old for discovery. A claim that drives a recommendation still needs evidence from a run or a page read during this audit.
5. On finish, write back the pages the report names with `addKeyPages` and append `{ updates: [{ appendResearchLog: { summary: "AI visibility audit: <run id>. Verdict: <conclusion>" } }] }`.

## OpenSEO MCP tools

The rest: https://github.com/every-app/open-seo/blob/HEAD/.agents/skills/ai-visibility-audit/SKILL.md