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 studiomeyer-io/studiomeyer-marketplace --skill geo-optimizationgit clone --depth 1 https://github.com/studiomeyer-io/studiomeyer-marketplaceWrote 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/studiomeyer-io/studiomeyer-marketplace/geo-optimization)<a href="https://agentmods.dev/skills/studiomeyer-io/studiomeyer-marketplace/geo-optimization"><img src="https://agentmods.dev/badge/skills/studiomeyer-io/studiomeyer-marketplace/geo-optimization/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/studiomeyer-io/studiomeyer-marketplace/geo-optimization"><img src="https://agentmods.dev/badge/skills/studiomeyer-io/studiomeyer-marketplace/geo-optimization.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 | $0.00066 | $0.01313 |
| Opus 5.5 | $0.00026 | $0.00525 |
| Sonnet 5.5 | $0.00013 | $0.00263 |
| Haiku 4.5 | $0.00007 | $0.00131 |
Grade A, and why
geo-optimization 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 1mo 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GEO Optimization Playbook
The StudioMeyer GEO server measures AI visibility across 8 LLM platforms and gives you the specific fixes to raise it. This skill is the map.
The GEO score (0-100)
Composed of six weighted sub-scores:
- Brand Awareness: does the LLM even know the brand?
- Citation Strength: when mentioned, is it cited with a link, or just name-dropped?
- Share of Voice: how often is the brand mentioned versus competitors in the same category?
- Sentiment: positive, neutral, or negative (negation-aware: "not bad" is positive)
- Discovery Stack: llms.txt, agents.json, JSON-LD, robots.txt all correct?
- Content Quality: citability signals (authority links, statistics, quotes,
sameAs)
Thresholds: 80 = excellent, 70 = good, below 50 = needs work.
Fix priority (cheapest to highest impact)
Tier 1: Discovery stack (free, ~1 day)
- llms.txt: machine-readable site description per llmstxt.org spec. Tells LLMs what your site is about and which URLs matter.
- agents.json: declare your site's AI capabilities (tools, endpoints, auth).
- robots.txt: check that GPTBot, ClaudeBot, PerplexityBot, Google-Extended are not blocked unless you have a reason. Especially watch for
/_next/disallow patterns that accidentally block bundled assets. - JSON-LD: Organization, WebSite, FAQPage schemas with recommended properties. Use
geo_schema_generatorto produce copy-paste-ready blocks. - Entity consistency: pick one canonical brand name and use it everywhere. "StudioMeyer", "Studio Meyer", "StudioMeyer.io" are three entities to an LLM.
Tier 2: Content quality (days to weeks)
- Authority links: link out to reputable sources from every substantive page. LLMs treat well-sourced pages as more citable.
- Statistics: concrete numbers with sources ("2.8x higher citation rate" with a link to the study) raise citability dramatically. KDD 2024 paper showed +30-40% citations when pages add stats + quotes.
- Quote blocks: named quotes from real people with attribution.
sameAslinks: Wikidata, Crunchbase, LinkedIn, GitHub. These are identity anchors LLMs use to cross-reference.- Content freshness:
dateModified, Last-Modified header, og:modified_time. Stale content gets down-weighted.
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.
- 1mo ago Changed d901a8b6a984
- 1mo ago First seen · 108 lines · 66 tokens per session scan A 21754368b410
geo-optimization is a skill published in the GitHub repository studiomeyer-io/studiomeyer-marketplace (2 stars, last pushed 6d ago), licensed MIT. It adds 66 tokens to every session and 1,313 once invoked, about $0.0003 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 2026-08-31.
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