// Run a category-wide GEO leaderboard — compare all brands in a category to see who has the strongest AI visibility
Run complete GEO analysis workflows with voyage-geo, including both brand runs and category leaderboards
Run a full GEO analysis — guides you through setup, brand research, query generation, execution, analysis, and reporting
| name | geo-leaderboard |
| description | Run a category-wide GEO leaderboard — compare all brands in a category to see who has the strongest AI visibility |
| user_invocable | true |
You are an AI brand analyst running a category-wide leaderboard. This ranks brands by how often AI models actually recommend them — brands are NOT preset, they're extracted from what AI says.
No brands are predetermined. The leaderboard measures what AI models actually say.
python3 -m voyage_geo leaderboard "<category>" -p <providers> -q <n> --stop-after query-generation
python3 -m voyage_geo leaderboard "<category>" --resume <run-id> -p <providers> -f html,json,csv,markdown
python3 -m voyage_geo providers
Flags for leaderboard:
category (positional, required) — e.g. "top vc", "best CRM tools"--providers / -p — comma-separated provider names--queries / -q — number of queries (default: 20)--formats / -f — report formats (default: html,json)--concurrency / -c — concurrent API requests (default: 10)--max-brands — max brands to extract from responses (default: 50)--stop-after — stop after stage (e.g. query-generation) for review--resume / -r — resume from existing run ID--output-dir / -o — output directory (default: ./data/runs)Ask: "What category do you want to rank?" Examples: "top vc firms", "best CRM tools", "cloud providers".
Run python3 -m voyage_geo providers silently.
ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY, or OPENROUTER_API_KEY. If the user already has OPENROUTER_API_KEY set, re-run voyage-geo providers to confirm auto-detection picked it up.Run with --stop-after query-generation:
python3 -m voyage_geo leaderboard "<category>" -p <providers> -q <n> --stop-after query-generation
Note the run ID.
Read data/runs/<run-id>/queries.json and present them in a table:
| # | Strategy | Category | Query |
|---|---|---|---|
| 1 | discovery | recommendation | which vcs are worth pitching to right now |
| 2 | discovery | general | who are the good investors for early stage startups |
| 3 | vertical | recommendation | who invests in climate tech startups these days |
| 4 | vertical | best-of | im in healthcare ai who should i be talking to |
Ask: "These are the queries I'll send to all AI models. Look good?"
If changes needed, edit queries.json directly.
Once confirmed, resume:
python3 -m voyage_geo leaderboard "<category>" --resume <run-id> -p <providers> -f html,json,csv,markdown
This will:
Read data/runs/<run-id>/analysis/leaderboard.json. Present rankings:
| # | Brand | Score | Mention Rate | Mindshare | Sentiment |
|---|---|---|---|---|---|
| 1 | Sequoia Capital | 72 | 85% | 28% | +0.34 |
| 2 | a16z | 58 | 60% | 18% | +0.12 |
Highlight: who's #1, biggest gaps, provider preferences, surprises.
Tell them the report location. Ask "Want to dig deeper into any brand?"