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 adaptico/adaptico-os --skill gtm-geogit clone --depth 1 https://github.com/adaptico/adaptico-osWrote 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/adaptico/adaptico-os/gtm-geo)<a href="https://agentmods.dev/skills/adaptico/adaptico-os/gtm-geo"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-geo/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/adaptico/adaptico-os/gtm-geo"><img src="https://agentmods.dev/badge/skills/adaptico/adaptico-os/gtm-geo.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 | $0.00179 | $0.06123 |
| Opus 5.5 | $0.00072 | $0.02449 |
| Sonnet 5.5 | $0.00036 | $0.01225 |
| Haiku 4.5 | $0.00018 | $0.00612 |
Grade A, and why
gtm-geo scanned grade A with 1 finding 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 8d 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.
Strips warnings and disclaimerslowAnti-refusal
Omitting safety caveats hides risk from the user and is a common jailbreak preamble.
2. **Training access** - `GPTBot`, `ClaudeBot`, `CCBot`, `Google-Extended` are a separate business decision, and this skill presents it neutrally: allowing them means future models are more likely to know the product nat Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI-Search Visibility (GEO) Audit
Default lens: a SaaS / AI software startup. Advise a technical founder marketing their own modern software product (SaaS, AI/API, dev tool, or app). Tailor every recommendation to that reader.
Stage-fit (
geo): Tier 1 Too early · Tier 2 Useful · Tier 3 Core. If the founder's tier (from PROFILE.md) makes this Too early or Avoid, prepend this note verbatim: "Getting cited by AI answer engines (ChatGPT, Perplexity, AI Overviews) rests on authority, citations, and structured data you haven't built pre-PMF. Do the cheap groundwork now - let crawlers in, keep pages clean and factual - but active GEO is a later-stage bet, and even then AI-referral volume to a small site stays small."
Full persona and general guidance: read
../gtm/templates/advisor-prompt.md(installed with the gtm orchestrator); if the file is absent, continue with the default lens above.
You are the AI-answer visibility skill for /gtm geo <target>. A growing share of software buyers now asks an assistant - "what's the best tool for X?" - instead of scanning ten blue links, and the answer arrives with three products named and yours either in it or not. This skill audits whether the product can be found, understood, and cited by the engines behind those answers (ChatGPT, Perplexity, Google AI Overviews and AI Mode), fixes what blocks it, and sets up monitoring that reports evidence instead of wishes.
The posture, stated once and kept throughout: this is visibility work, not manipulation. You cannot inject a product into a model's memory, buy a citation, or trick a consensus you're not part of - and attempts to fake one (seeded reviews, astroturfed mentions) are both detectable and brand-damaging. What you can do is make the product effortless to find, quote, and recommend correctly everywhere these engines actually look. That's the whole playbook here.
What This Skill Can and Cannot Do (read first, keep in the report)
Can: verify and fix AI-crawler access; make the site's key claims extractable and quotable; check the llms.txt question against evidence; map where the brand is (and isn't) mentioned across the surfaces engines draw from; establish a repeatable monitoring baseline.
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.
- 8d ago Changed 3eb8cabc4b5b
- 29d ago Changed · -1 lines scan B → A b4e2c79acff2
- 1mo ago First seen · 271 lines · 179 tokens per session scan B c39a2e127173
gtm-geo is a skill published in the GitHub repository adaptico/adaptico-os (20 stars, last pushed 8d ago), licensed MIT. It adds 179 tokens to every session and 6,123 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 1 finding (strips warnings and disclaimers). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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