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 featuresgit 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/features)<a href="https://agentmods.dev/skills/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/features"><img src="https://agentmods.dev/badge/skills/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/features/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/features"><img src="https://agentmods.dev/badge/skills/ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool/features.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 | $0.00426 |
| Opus 5.5 | $0.00007 | $0.00170 |
| Sonnet 5.5 | $0.00003 | $0.00085 |
| Haiku 4.5 | $0.00002 | $0.00043 |
Grade A, and why
features 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:
- features — 100% identical, 0 lines differ
What it actually says
How AI compares us
How AI engines describe the brand against each tracked competitor, feature by feature, in the engines' own words.
When to use
- "Which features does AI name for Northwind but not for us?", "How does ChatGPT compare us with our rivals?"
- For a page that answers "X or Y?", the Comparison page skill fits better.
What to read
list_competitors, andget_competitor_comparisonfor the period: who the brand is compared with, and where each leads.get_mention_competitors: the competitors named beside the brand most often.list_mentions, thenget_mentionfor answers that name the brand and a competitor together: what each is praised or faulted for.get_mentions_perception: what AI associates with the brand.
Steps
- Take the competitor the person names; with none, the two or three named beside the brand most.
- List the features and qualities the answers name, for the brand and for each competitor.
- For each one: who AI credits with it, with a short quote and its engine.
- Mark the features AI names for a competitor but never for the brand, and anything AI says about the brand that looks wrong.
Output
- A table: Feature, the brand, one column per competitor, Quote and engine.
- "Gaps": the features AI credits only to competitors, and what to check for each.
- Claims about the brand that look wrong, for the person to confirm.
Don't
- Don't decide which product is better: report what AI says.
- Never state what the brand offers from your own knowledge: ask the person.
- Don't disparage a competitor, and claim nothing about them an answer doesn't say.
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 · 44 lines · 17 tokens per session scan A a4d2f6cae5dd
features 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 426 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.
features compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| featuresai-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 |