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 ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool --skill listingsgit clone --depth 1 https://github.com/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-toolWrote 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/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/listings)<a href="https://agentmods.dev/skills/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/listings"><img src="https://agentmods.dev/badge/skills/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/listings/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/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/listings"><img src="https://agentmods.dev/badge/skills/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/listings.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 | $0.00017 | $0.00416 |
| Opus 5.5 | $0.00007 | $0.00166 |
| Sonnet 5.5 | $0.00003 | $0.00083 |
| Haiku 4.5 | $0.00002 | $0.00042 |
Grade A, and why
listings 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 yesterday.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- listings — 100% identical, 0 lines differ
What it actually says
Listing gaps
The directories, marketplaces, review sites and publishers AI engines cite in the brand's category, and whether each one lists the brand.
When to use
- "Which directories and review sites does AI trust in our category?", "Where are we missing?", "Publisher sites."
- To fix what AI gets wrong about the brand, the Fix wrong claims about us skill fits better.
What to read
list_citationswith the external filter: the third-party sites AI cites for the brand's prompts, and how often.list_ai_answersfor the prompts that cite them: which brands those answers recommend.list_competitors: the competitors to look for on each site.fetch_pagefor each site's page about the category: whether it names the brand.
Steps
- Take the market the person names; with none, every market the brand tracks.
- List the third-party sources AI cites most, by kind: directory, marketplace, review site, publisher.
- For each: the answers that cite it, and the competitors it names.
- Read its page to see whether it lists the brand. When the page can't be read, write "unknown".
- Suggest a next step for each: ask for a listing, update a profile, or nothing to do.
Output
- A table: Source, Kind, Answers citing it, Lists you, Competitors listed, Next step.
- Outreach drafts for the top three, when the person asks.
- Sending leaves the workspace: the person does it. Chat sends nothing.
Don't
- Never say a site lists the brand, or doesn't, without reading its page.
- Don't invent contacts, names or addresses for outreach.
- Never promise a listing will bring citations.
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.
- yesterday First seen · 45 lines · 17 tokens per session scan A f251921c80b5
listings is a skill published in the GitHub repository ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool (449 stars, last pushed yesterday), licensed MIT. It adds 17 tokens to every session and 416 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 2026-11-05.
listings compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| listingsai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool | Skill | 449 | yesterday | MIT | A | 17 | Claude Code, Codex |
| geo-platform-optimizerasale-ai/seo-geo-skill | Skill | 6 | 2mo ago | none | A | 34 | Claude Code |
| ansvisor-aeo-coach-standaloneansvisor/ansvisor | Skill | 232 | yesterday | MIT | A | 148 | Claude Code, Codex |
| geo-loopmverab/eGEOagents | Skill | 217 | yesterday | MIT | A | 62 | Claude Code |
| content-scoringmverab/eGEOagents | Skill | 217 | yesterday | MIT | A | 34 | Claude Code |
| competitive-analysismverab/eGEOagents | Skill | 217 | yesterday | MIT | A | 29 | Claude Code |
| schema-generatormverab/eGEOagents | Skill | 217 | yesterday | MIT | A | 35 | Claude Code |