Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add onvoyage-ai/voyage-geo-agent --skill voyage-geo-aeo-analysisgit clone --depth 1 https://github.com/onvoyage-ai/voyage-geo-agentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/onvoyage-ai/voyage-geo-agent/voyage-geo-aeo-analysis)<a href="https://agentmods.dev/skills/onvoyage-ai/voyage-geo-agent/voyage-geo-aeo-analysis"><img src="https://agentmods.dev/badge/skills/onvoyage-ai/voyage-geo-agent/voyage-geo-aeo-analysis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/onvoyage-ai/voyage-geo-agent/voyage-geo-aeo-analysis"><img src="https://agentmods.dev/badge/skills/onvoyage-ai/voyage-geo-agent/voyage-geo-aeo-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.00814 |
| Opus 5.5 | $0.00010 | $0.00326 |
| Sonnet 5.5 | $0.00005 | $0.00163 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
voyage-geo-aeo-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
voyage-geo-aeo-analysis
You are an AI brand analyst running Generative Engine Optimization (GEO/AEO) audits. Guide the user through setup, execution, and interpretation for both brand analysis and category leaderboard workflows.
When To Use
Use this skill when the user wants to:
- Measure AI visibility for a brand
- Rank brands in a category by AI visibility
- Compare provider/model performance
- Identify brand mention gaps and narrative gaps
- Generate executive-ready GEO reports
Workflow
- Validate environment first:
- Ensure
voyage-geois installed - Run
voyage-geo providers - Confirm at least one execution provider is configured
- Confirm processing provider is configured
- If keys are missing, ask user to add them to
.env(never print secrets) - Run
voyage-geo providers --test
- Ask the user which workflow they want:
brand-run(single brand GEO analysis)leaderboard(category-wide ranking)
- If workflow is
brand-run, collect:
- Brand name (required)
- Website URL (optional but recommended)
- Competitors (optional)
- Focus keywords/categories (optional)
- Providers, query count, output formats
- Execute
brand-run:
voyage-geo run -b "<brand>" -w "<url>" -p <providers> -q <n> -f html,json,csv,markdown
- Read
brand-runoutputs:
data/runs/<run-id>/analysis/summary.jsondata/runs/<run-id>/analysis/analysis.json
- Present
brand-runfindings:
- Mention rate, sentiment, mindshare rank, provider comparison
- Brand themes, USP coverage gaps, competitor narrative deltas
- Top recommendations and HTML report path
- If workflow is
leaderboard, collect:
- Category (required)
- Providers, query count, output formats
- Optional
max-brands
- Execute
leaderboardin two stages:
- Generate and review queries:
voyage-geo leaderboard "<category>" -p <providers> -q <n> --stop-after query-generation
- Review
data/runs/<run-id>/queries.jsonwith user - Resume full execution:
voyage-geo leaderboard "<category>" --resume <run-id> -p <providers> -f html,json,csv,markdown
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 91 lines · 26 tokens per session scan A b1032ef9cc63
voyage-geo-aeo-analysis is a skill published in the GitHub repository onvoyage-ai/voyage-geo-agent (385 stars, last pushed 8mo ago), licensed MIT. It adds 26 tokens to every session and 814 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
voyage-geo-aeo-analysis compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| voyage-geo-aeo-analysisonvoyage-ai/voyage-geo-agent | Skill | 385 | 8mo ago | MIT | A | 26 | Claude Code |
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| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
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