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 surendranb/google-analytics-mcp --skill geo-device-segmentationgit clone --depth 1 https://github.com/surendranb/google-analytics-mcpWrote 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/surendranb/google-analytics-mcp/geo-device-segmentation)<a href="https://agentmods.dev/skills/surendranb/google-analytics-mcp/geo-device-segmentation"><img src="https://agentmods.dev/badge/skills/surendranb/google-analytics-mcp/geo-device-segmentation.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00031 | $0.00638 |
| Opus 5 | $0.00015 | $0.00319 |
| Sonnet 5 | $0.00006 | $0.00128 |
| Haiku 4.5 | $0.00003 | $0.00064 |
Grade A, and why
geo-device-segmentation 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 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.
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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Geo and Device Segmentation
Break down user behaviour by country, city, device category, and OS to understand regional patterns and optimise for your key markets.
Correct dimension names
| Concept | GA4 API name |
|---|---|
| Country | country |
| City | city |
| Region | region |
| Device category | deviceCategory |
| Operating system | operatingSystem |
| OS version | operatingSystemVersion |
| Browser | browser |
| Screen resolution | screenResolution |
| Language | language |
Device category values: desktop, mobile, tablet.
Step 1 — Country breakdown
dimensions: ["country"]
metrics: ["totalUsers", "sessions", "userEngagementDuration",
"screenPageViewsPerSession", "keyEvents"]
date_range: last 30 days
order_by: totalUsers DESC
limit: 20
Step 2 — Device split
dimensions: ["deviceCategory"]
metrics: ["sessions", "totalUsers", "engagementRate",
"userEngagementDuration", "bounceRate"]
date_range: last 30 days
order_by: sessions DESC
Step 3 — Country + device cross-tab
Understand device preferences by market:
dimensions: ["country", "deviceCategory"]
metrics: ["sessions", "userEngagementDuration", "bounceRate"]
dimension_filter: country IN [your top 5 countries from Step 1]
date_range: last 30 days
order_by: sessions DESC
Note: combining country + deviceCategory + additional dimensions in one query may exceed GA4's cardinality limit. Keep to 2–3 dimensions max.
Step 4 — Single-country deep dive
For a specific country (e.g. Japan):
dimensions: ["city", "deviceCategory"]
metrics: ["sessions", "totalUsers", "userEngagementDuration", "keyEvents"]
dimension_filter: {
"filter": {
"fieldName": "country",
"stringFilter": {"matchType": "EXACT", "value": "Japan"}
}
}
date_range: last 30 days
order_by: sessions DESC
limit: 20
Step 5 — Browser and OS (for technical optimisation)
dimensions: ["browser", "operatingSystem", "deviceCategory"]
metrics: ["sessions", "bounceRate", "userEngagementDuration"]
date_range: last 30 days
order_by: sessions DESC
limit: 20
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 First seen · 89 lines · 31 tokens per session scan A d562847e7a85
geo-device-segmentation is a skill published in the GitHub repository surendranb/google-analytics-mcp (241 stars, last pushed 6d ago), licensed MIT. It adds 31 tokens to every session and 638 once invoked, about $0.0002 per session on Opus 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.
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