aeo-visibility

AEO Visibility Checker

Check how visible your company is across AI answer engines (ChatGPT, Claude, Gemini, Perplexity).

What It Does

1. Profile a company: Research the company, discover competitors, generate ~100 test queries
2. Run visibility check: Query all 4 engines with your queries, analyze mentions/prominence/sentiment
3. Generate reports: Markdown report + CSV export with full metrics
4. Track history: Maintain historical runs to track visibility trends over time

Usage

1. Profile a Client

node src/cli.js profile <client-name> [--url=https://example.com]

This will:

• Research the company (via web_search in production)
• Discover competitors automatically
• Generate ~100 diverse search queries
• Save to clients/<client-name>/profile.json and queries.json

Review and edit queries.json before running.

2. Run Full Check

node src/cli.js run <client-name>

Runs all queries against all 4 engines. Creates:

• clients/<client-name>/runs/YYYY-MM-DD-HHMM/report.md (detailed markdown report)
• clients/<client-name>/runs/YYYY-MM-DD-HHMM/results.csv (full data export)
• clients/<client-name>/runs/YYYY-MM-DD-HHMM/raw-responses.json (raw API responses)
• Updates clients/<client-name>/history.csv (summary of all runs)

Cost: ~$10-30 per full run (100 queries × 4 engines × ~$0.025-0.075/query)

3. Run Specific Queries (Granular)

node src/cli.js run <client-name> --queries "best AI tools" "top LLMs for coding" "AI assistants"

Test specific queries only (cheaper, faster).

4. View History

node src/cli.js history <client-name>

Shows all historical runs with key metrics.

Report Contents

Markdown Report (report.md)

• Executive summary: Total mentions, avg visibility score, top engine
• Performance by engine: Mention rate, prominent mentions, avg sentiment
• Competitor comparison: How often competitors are mentioned vs you
• Top performing queries: Queries where you're mentioned most
• Missed opportunities: Queries where competitors are mentioned but you're not

CSV Export (results.csv)

Raw data with columns:

• query
• mentioned (yes/no per engine)
• prominence (high/medium/low per engine)
• sentiment (-1 to 1 per engine)
• competitors_mentioned

Analysis Metrics

Mentioned: Is the company mentioned in the response at all?

Prominence:

• High: Mentioned in first 2 sentences (top of mind)
• Medium: Mentioned in middle of response
• Low: Mentioned at end or as footnote

Sentiment: -1 to 1 scale

• 1 = Very positive
• 0 = Neutral
• -1 = Negative

Multi-Client Support

Results are saved to the workspace-level client directory (not inside the skill):

clients/
├── acme-corp/
│   └── aeo-visibility-reports/
│       ├── profile.json
│       ├── queries.json
│       ├── runs/
│       │   ├── 2026-02-25T02-00-00/
│       │   └── 2026-03-01T10-30-00/
│       └── history.csv
└── other-client/
    └── aeo-visibility-reports/
        └── ...

Environment Variables Required

export OPENAI_API_KEY=...
export ANTHROPIC_API_KEY=...
export GOOGLE_API_KEY=...
export PERPLEXITY_API_KEY=...

Integration with OpenClaw

This skill is designed to be triggered via OpenClaw chat:

"Can you check our AEO visibility?"
"Run visibility check for acme-corp"
"Check how we rank for AI coding tools on answer engines"

OpenClaw agent will:

1. Call profile command if client not yet set up
2. Present generated queries for review
3. Run visibility check after approval
4. Summarize results from report

Cost Management

• Full run: $10-30 (100 queries × 4 engines)
• Granular run: ~$0.10-0.30 per query × 4 engines
• Profiling: ~$0.50 (competitor discovery + query generation)

The CLI shows cost estimate before running.

Future Enhancements

• Add more engines (Gemini Deep Research, SearchGPT)
• Weekly scheduled runs with trend alerts
• Optimize query set based on performance
• A/B test different query phrasings
• Auto-generate optimization recommendations