traffic-diagnosis

traffic-diagnosis is a skill for Claude Code from surendranb/google-analytics-mcp. It costs 34 tokens per session (692 once invoked), scanned A, original, MIT.

A step-by-step procedure for finding why website traffic increased, decreased, or changed between visitor groups. It compares metrics such as sessions and users across time and traffic sources.

In plain words
What is it for?
Use it to investigate traffic spikes, drops, or shifts in source mix. It compares equivalent periods, identifies the channel responsible, and checks recent daily patterns for likely causes.
Why use it?
It turns a general traffic change into narrower, testable possibilities by checking the baseline, affected channel, timing, and other dimensions. This helps distinguish sudden events from gradual changes.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the google-analytics-mcp plugin — 18 skills, 1 MCP server shipped together

Good fit Use it to investigate traffic spikes, drops, or shifts in source mix. It compares equivalent periods, identifies the channel responsible, and checks recent daily patterns for likely causes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/surendranb/google-analytics-mcp/traffic-diagnosis
Install

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.

Any agent
npx skills add surendranb/google-analytics-mcp --skill traffic-diagnosis
Clone the repo
git clone --depth 1 https://github.com/surendranb/google-analytics-mcp

Made for: Claude Code.

Or install google-analytics-mcp, the plugin that ships this one along with the rest of its 18 skills, 1 MCP server.

Wrote 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.

agentmods badge for traffic-diagnosis

README.md
[![agentmods](https://agentmods.dev/badge/skills/surendranb/google-analytics-mcp/traffic-diagnosis/github.svg)](https://agentmods.dev/skills/surendranb/google-analytics-mcp/traffic-diagnosis)
Your own site
<a href="https://agentmods.dev/skills/surendranb/google-analytics-mcp/traffic-diagnosis"><img src="https://agentmods.dev/badge/skills/surendranb/google-analytics-mcp/traffic-diagnosis/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.

agentmods 80×15 button for traffic-diagnosis

Your own site · 80×15
<a href="https://agentmods.dev/skills/surendranb/google-analytics-mcp/traffic-diagnosis"><img src="https://agentmods.dev/badge/skills/surendranb/google-analytics-mcp/traffic-diagnosis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 692 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00034 $0.00692
Opus 5.5 $0.00014 $0.00277
Sonnet 5.5 $0.00007 $0.00138
Haiku 4.5 $0.00003 $0.00069

Measured 2mo ago against content hash 8e267b5e6188, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

traffic-diagnosis 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 2mo 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.

skills/traffic-diagnosis/SKILL.md · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Traffic Change Diagnosis

Systematically diagnose why traffic changed — spike, drop, or shift in mix. Follow these steps in order. Each step narrows the hypothesis.

Step 1 — Establish the baseline

Compare the period in question to the equivalent prior period:

dimensions: ["date"]
metrics: ["sessions", "totalUsers", "newUsers", "engagedSessions", "keyEvents"]
date_range: affected period + same-length prior period

Measure: absolute change, % change, and whether all metrics moved together. If sessions dropped but engagement rate improved, volume dropped but quality held — different cause than if everything dropped proportionally.

Step 2 — Isolate which channel changed

dimensions: ["sessionDefaultChannelGroup"]
metrics: ["sessions", "totalUsers", "engagedSessions", "engagementRate"]
date_range: affected period vs prior period

Which channel account for most of the change? Narrow to that channel before going deeper.

Step 3 — Check time pattern (sudden vs gradual)

dimensions: ["date", "sessionDefaultChannelGroup"]
metrics: ["sessions"]
date_range: last 28 days
  • Sudden single-day spike/drop → campaign launch/end, deploy, media mention, bot flood
  • Gradual decline over weeks → SEO decay, seasonal drift, quality score drop
  • Step change that persists → tracking change, filter change, channel definition update

Step 4 — Fingerprint the cause

Run queries matching the suspected cause:

Bot flood — see bot-traffic-detection skill:

  • engagementRate near 0, averageSessionDuration ≈ 0
  • Unusual hostname or country concentration

Campaign start/end:

dimensions: ["sessionCampaignName", "sessionSource", "sessionMedium"]
metrics: ["sessions", "keyEvents", "engagementRate"]
dimension_filter: sessionDefaultChannelGroup IN ["Paid Search", "Paid Social", "Display"]

SEO change (organic):

dimensions: ["sessionDefaultChannelGroup", "landingPagePlusQueryString"]
metrics: ["sessions", "engagementRate", "keyEvents"]
dimension_filter: sessionDefaultChannelGroup = "Organic Search"
date_range: 90 days (to see gradual trend)

Read the full file on GitHub · 85 lines

Changes

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.

  1. 2mo ago First seen · 85 lines · 34 tokens per session scan A 8e267b5e6188

Subscribe to this mod's changes

traffic-diagnosis is a skill published in the GitHub repository surendranb/google-analytics-mcp (244 stars, last pushed 5d ago), licensed MIT. It adds 34 tokens to every session and 692 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 2026-08-30.

Related

traffic-diagnosis compared with skills from other repositories

traffic-diagnosis next to 6 skills from other repositories
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