agentleFS
Sign inStart free
arcbaslowarcbaslow/google-analytics-agent/skills/ga4-segments/SKILL.md

ga4-segments

Skill0 starsChanged 6 months agoMITView on GitHub

GA4 funnel drop-off cohort analysis. Breaks down each funnel step by device, source/medium, country, landing page, new-vs-returning. Funnel steps are taken from the caller and the analysis is taxonomy-agnostic. Use when user says 'segment', 'cohort', 'which devices', 'which channels', 'why is segment X lower'.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 0 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Default all: device, channel group, source, medium, country, landing page, new-vs-returning.

    line 22
  2. Very specific:

    If a recent ga4-quality run reports sampling >10% or (not set) density >20% on a dimension, the agent will mark that breakdown as …

    line 28

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

GA4 Funnel Segment Analysis

Process

  1. Verify auth
  2. Spawn ga4-segments agent

Breakdowns

Default all: device, channel group, source, medium, country, landing page, new-vs-returning.

Override with --breakdown <dim> to run a single dimension.

Confidence inheritance

If a recent ga4-quality run reports sampling >10% or (not set) density >20% on a dimension, the agent will mark that breakdown as "directional only" in output.

After analysis

Offer: "Want to drill into a specific segment? Re-run with --breakdown <dim> for the dimension that caught your eye."

Parameter aggregate metrics return coverage_pct: null with status: not_measurable; positive revenue is not proof of complete tagging. Segment audits use the API sessionKeyEventRate and label findings session_key_event_rate.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free