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 agentmods add skills/surendranb/google-analytics-mcp/content-performancenpx skills add surendranb/google-analytics-mcp --skill content-performancegit 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/content-performance)<a href="https://agentmods.dev/skills/surendranb/google-analytics-mcp/content-performance"><img src="https://agentmods.dev/badge/skills/surendranb/google-analytics-mcp/content-performance.svg" alt="Measured on agentmods" 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 | $0.00022 | $0.00614 |
| Opus 5 | $0.00011 | $0.00307 |
| Sonnet 5 | $0.00004 | $0.00123 |
| Haiku 4.5 | $0.00002 | $0.00061 |
Grade A, and why
content-performance 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 4d 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Performance Analysis
Identify top-performing pages, find underperforming content, and understand engagement patterns across your site.
When to use
- You want to know which pages drive the most traffic and engagement
- You want to find pages with high views but low engagement (poor content fit)
- You want to identify content that drives conversions or return visits
Correct dimension and metric names
| Concept | GA4 API name |
|---|---|
| Page path | pagePath |
| Page title | pageTitle |
| Landing page | landingPage |
| Page views | screenPageViews |
| Unique page views (users) | totalUsers |
| Engagement rate | engagementRate |
| Avg engagement time | userEngagementDuration |
| Scroll depth | scrolledUsers (if scroll event is tracked) |
| Entries (landing views) | sessions with landingPage dimension |
Do not use pageviews — the correct metric is screenPageViews.
Step 1 — Top pages by traffic
dimensions: ["pagePath", "pageTitle"]
metrics: ["screenPageViews", "totalUsers", "userEngagementDuration",
"engagementRate", "bounceRate"]
date_range: last 30 days
order_by: screenPageViews DESC
limit: 25
Step 2 — Landing page performance
Which pages do users enter your site through, and how well do they engage:
dimensions: ["landingPage"]
metrics: ["sessions", "newUsers", "userEngagementDuration",
"engagementRate", "keyEvents"]
date_range: last 30 days
order_by: sessions DESC
limit: 25
Step 3 — Underperforming content (high views, low engagement)
Run Step 1, then flag pages where:
screenPageViewsis in the top 50% ANDengagementRateis below 0.3 (30%) ORuserEngagementDuration< 30 seconds
These pages attract traffic but fail to hold attention — candidates for content improvement or better internal linking.
Step 4 — Content trend over time
dimensions: ["date", "pagePath"]
metrics: ["screenPageViews", "totalUsers"]
dimension_filter: pagePath contains "/blog" (or your content path)
date_range: last 90 days
order_by: date ASC
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.
- 4d ago First seen · 74 lines · 22 tokens per session scan A dad8173f5b74
content-performance is a skill published in the GitHub repository surendranb/google-analytics-mcp (240 stars, last pushed 2d ago), licensed MIT. It adds 22 tokens to every session and 614 once invoked, about $0.0001 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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