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Agent skill

Analytics Tracking Automation

by jtrackingai in jtrackingai/analytics-tracking-automation

A skill your agent uses when you need GA4 + GTM tracking delivery from site discovery through publish, or when the right phase entry point is still unclear.

Apache-2.0Auto-check passedData & Analytics

Install Analytics Tracking Automation

skills CLI
$ npx skills add jtrackingai/analytics-tracking-automation --skill analytics-tracking-automation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jtrackingai/analytics-tracking-automation analytics-tracking-automation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
analytics-tracking-automation
GitHub stars
142
Token cost
~2.8k tokens
SKILL.md length
1,264 words
Files
115 (incl. scripts, references)
Skills in repo
8
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when you need GA4 + GTM tracking delivery from site discovery through publish, or when the right phase entry point is still unclear.

  • Works in 5 steps: Resolve the directory that contains this… → Run node… → If the result status is… → …
  • You need GA4 + GTM tracking delivery from site discovery through publish
  • SKILL.md covers Auto-Update, Skill Family, Shared Contract and Conversation Intake, plus 4 more sections
  • Calls node, npm and npx

What it does

Analytics Tracking Automation is an agent skill from jtrackingai/analytics-tracking-automation. Use when you need GA4 + GTM tracking delivery from site discovery through publish, or when the right phase entry point is still unclear.

Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 119 other files, including scripts and reference files (for example `.github/ISSUE_TEMPLATE/bug_report.md`, `.github/ISSUE_TEMPLATE/config.yml` and `.github/ISSUE_TEMPLATE/feature_request.md`). Compatibility notes: Requires Node.js 18+, npm, and Playwright Chromium for browser-backed steps. analyze, validate-schema --check-selectors, preview, and sync each launch a real…

It sits in Data & Analytics, covering Product analytics and Go-to-market strategy. It works with Google Analytics and Shopify. The repository describes itself as: AI-powered GA4 + GTM event tracking — automates site analysis, event schema, GTM sync, preview verification, and publishing. Works with Cursor, Codex, and any AI agent. The licence is Apache-2.0.

When your agent uses it

  • You need GA4 + GTM tracking delivery from site discovery through publish
  • The right phase entry point is still unclear

Example prompts

  • “/analytics-tracking-automation”

Requirements

  • Node.js
  • Compatibility (from SKILL.md): Requires Node.js 18+, npm, and Playwright Chromium for browser-backed steps. analyze, validate-schema --check-selectors, preview, and sync each launch a real Chromium and/or call Google's GTM API, so they need outbound HTTP, local browser execution, and (for sync) a local loopback callback on 127.0.0.1 to receive Google's OAuth consent redirect. Run them in an environment that provides those capabilities. sync uses Google's interactive OAuth consent screen; the resulting user-owned refresh token is stored under the artifact directory and read locally by sync, preview, and publish when they call the official GTM API. A minimal anonymous startup signal is sent when the CLI command begins so operators can measure active usage. Richer anonymous diagnostics remain opt-in, are used only to improve the skill experience and workflow quality, and are not used for sensitive actions or sensitive behavior tracking.

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Resolve the directory that contains this installed SKILL.md. Installer-managed copies usually live under the skills directory configured…
  2. Run node "/runtime/skill-runtime/update-check.mjs" --json.
  3. If the result status is update_available, immediately run node "/runtime/skill-runtime/self-update.mjs" --apply.
  4. If the update succeeds, read /SKILL.md again before continuing so you are using the refreshed instructions.
  5. If the result status is disabled, treat this bundle as a local development link or repo checkout and continue without updating.

What it can do on your machine

Read from SKILL.md and the folder at commit 68378e0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/, which the agent can run.

    Shell commands in SKILL.md call:

    • node
    • npm
    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npm and npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Requires Node.js 18+, npm, and Playwright Chromium for browser-backed steps. analyze, validate-schema --check-selectors, preview, and sync each launch a real Chromium and/or call Google's GTM API, so they need outbound HTTP, local browser execution, and (for sync) a local loopback callback on 127.0.0.1 to receive Google's OAuth consent redirect. Run them in an environment that provides those capabilities. sync uses Google's interactive OAuth consent screen; the resulting user-owned refresh token is stored under the artifact directory and read locally by sync, preview, and publish when they call the official GTM API. A minimal anonymous startup signal is sent when the CLI command begins so operators can measure active usage. Richer anonymous diagnostics remain opt-in, are used only to improve the skill experience and workflow quality, and are not used for sensitive actions or sensitive behavior tracking.

    From compatibility in the SKILL.md frontmatter.

Context cost

Analytics Tracking Automation loads about 2.8k tokens when it runs, and up to ~21k if it reads all its reference files. Until then it costs about 42 tokens; SKILL.md has 1,264 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
When it runs · the whole SKILL.md, loaded when a task matches
~2.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~21k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from jtrackingai/analytics-tracking-automation at commit 68378e0, republished under its Apache-2.0 licence (© jtrackingai). 1,264 words, ~2,752 tokens.

Download SKILL.mdSave it as .claude/skills/analytics-tracking-automation/SKILL.md (or your agent's skills folder). This skill also uses 114 other files; get the full folder from GitHub.
name
analytics-tracking-automation
description
Use when you need GA4 + GTM tracking delivery from site discovery through publish, or when the right phase entry point is still unclear.
compatibility
Requires Node.js 18+, npm, and Playwright Chromium for browser-backed steps. analyze, validate-schema --check-selectors, preview, and sync each launch a real Chromium and/or call Google's GTM API, so they need outbound HTTP, local browser execution, and (for sync) a local loopback callback on 127.0.0.1 to receive Google's OAuth consent redirect. Run them in an environment that provides those capabilities. sync uses Google's interactive OAuth consent screen; the resulting user-owned refresh token is stored under the artifact directory and read locally by sync, preview, and publish when they call the official GTM API. A minimal anonymous startup signal is sent when the CLI command begins so operators can measure active usage. Richer anonymous diagnostics remain opt-in, are used only to improve the skill experience and workflow quality, and are not used for sensitive actions or sensitive behavior tracking.

Analytics Tracking Automation

Use this skill as the end-to-end coordinator for GA4 + GTM tracking delivery.

Use it when:

  • the user needs a full GA4 + GTM implementation flow, from analysis to go-live readiness
  • the request spans multiple workflow phases (discovery, schema, sync, verification, publish)
  • the correct entry point is still unclear and you need this skill to route to the right phase

Do not assume the user wants the full workflow.

<!-- analytics-tracking-automation auto-update bootstrap:start -->

Auto-Update

This installed root skill can self-check for newer GitHub versions before you continue.

Before doing any task in this bundle:

  1. Resolve the directory that contains this installed SKILL.md. Installer-managed copies usually live under the skills directory configured by your agent environment, such as $CODEX_HOME/skills/analytics-tracking-automation or an equivalent runtime-managed path.
  2. Run node "<bundle-dir>/runtime/skill-runtime/update-check.mjs" --json.
  3. If the result status is update_available, immediately run node "<bundle-dir>/runtime/skill-runtime/self-update.mjs" --apply.
  4. If the update succeeds, read <bundle-dir>/SKILL.md again before continuing so you are using the refreshed instructions.
  5. If the result status is disabled, treat this bundle as a local development link or repo checkout and continue without updating.
<!-- analytics-tracking-automation auto-update bootstrap:end -->

Skill Family

The skill family is split into one umbrella skill plus seven phase skills:

  • tracking-discover for crawl coverage, platform detection, and fresh artifact bootstrap
  • tracking-group for page-group authoring and approval
  • tracking-live-gtm for auditing the real live GTM runtime before schema generation
  • tracking-schema for schema preparation, review, validation, and approval
  • tracking-sync for GTM config generation and sync
  • tracking-verify for preview QA and optional publish handoff
  • tracking-shopify for Shopify-specific schema, sync, install, and verification rules

If the request is already bounded to one phase and that phase skill is available, route there instead of inlining the full runbook here.

Once site-analysis.json indicates Shopify, keep discovery and grouping shared, then let tracking-shopify own the Shopify-specific branch.

Shared Contract

  • Use the repo-local wrapper ./event-tracking in this repository. If dist/cli.js is missing, run npm run build first.
  • For public/ClawHub installs, you must run this first before any event-tracking command: npx skills add jtrackingai/analytics-tracking-automation.
  • Keep one artifact directory per site at <output-root>/<url-slug>.
  • If the user already provides an artifact directory or one of its files, resume from the earliest unmet prerequisite instead of restarting from analyze.
  • Use ./event-tracking status <artifact-dir-or-file> whenever the current checkpoint or next step is unclear.
  • Use ./event-tracking runs <output-root> when the artifact directory is unknown but the output root is known.
  • Prefer high-level entry commands for user-facing flows: run-new-setup, run-tracking-update, run-upkeep, run-health-audit.
  • Telemetry consent is a required user-choice checkpoint for richer diagnostics. If consent is unanswered when any workflow command surfaces the prompt, stop and follow telemetry-consent.md as the single-source interaction contract. Never decide yes/no on the user's behalf, and continue through the interactive prompt so the local config records their choice.
  • Explain the purpose, what yes does, what no does, and the remaining privacy tradeoff before asking the user to reply yes or no. Do not ask a bare yes/no question with no context.
  • Treat workflow mode metadata as an internal workflow-state layer, not a user-facing command surface.
  • analyze, validate-schema --check-selectors, preview, and sync each need outbound HTTP and a real Chromium; sync additionally needs a local loopback callback on 127.0.0.1 for Google's OAuth consent redirect. Run them in an environment that permits those capabilities so Playwright and the OAuth callback can complete.
  • Run prompt-driven GTM sync with an interactive TTY from the start unless exact --account-id, --container-id, and --workspace-id values are already confirmed.
  • Never auto-select a GTM account, container, or workspace on the user's behalf.
  • Do not continue past the phase boundary the user asked for.

Conversation Intake

When the user enters through chat and has not yet provided a bounded phase, artifact directory, or exact command, start with an intent-first intake.

Classify the request into one of these entry intents:

  • resume_existing_run: the user already has an artifact directory or one of its files; inspect the artifacts and use status
  • new_setup: net-new tracking implementation from scratch; prefer run-new-setup, then follow its recommended next step
  • tracking_update: revise or extend an existing implementation; prefer run-tracking-update
  • upkeep: routine maintenance, review, or incremental QA on an existing setup; prefer run-upkeep
  • tracking_health_audit: audit-only assessment of current live tracking; prefer run-health-audit
  • analysis_only: crawl/bootstrap/discovery only without committing to the full workflow yet; route to tracking-discover and stop after analyze

Rules:

  • Do not ask the user to choose between internal workflow metadata flags and analyze.
  • If intent is ambiguous, ask one short plain-language intake question using user-facing terms such as "new setup", "update existing tracking", "upkeep", "health audit", "analyze only", or "resume an existing run".
  • If the user gives a fresh URL and asks to set up tracking, default to new_setup.
  • If the user gives a fresh URL and only asks to inspect the site, analyze structure, or review current tracking signals, default to analysis_only.
  • If the user gives an artifact directory or workflow file, default to resume_existing_run instead of restarting from analyze.
Show full SKILL.md (461 more words)Show less

Routing Rules

Route by user intent and current artifacts:

  • fresh URL, crawl request, or no artifacts yet: start with tracking-discover
  • site-analysis.json with missing or unconfirmed pageGroups: route to tracking-group
  • confirmed site-analysis.json with detected live GTM container IDs but no live baseline review yet: route to tracking-live-gtm
  • confirmed site-analysis.json or an in-progress event-schema.json: route to tracking-schema
  • approved event-schema.json without gtm-config.json: route to tracking-sync for generate-gtm
  • gtm-config.json: route to tracking-sync
  • gtm-context.json: route to tracking-verify, with publish treated as a separate explicit action
  • Shopify platform confirmation: keep shared early stages, then hand off to tracking-shopify

If only the root skill is available, follow the same routing logic directly and stop at the matching phase boundary.

Stop Rules

  • Do not bypass page-group approval before prepare-schema.
  • For key decision checkpoints, always require explicit user confirmation before continuing:
    • pageGroups (before confirm-page-groups and before prepare-schema)
    • event-schema.json (before confirm-schema and before generate-gtm)
    • GTM target selection (account/container/workspace during sync)
    • publish decision (before publish)
  • If confirmation is missing or ambiguous, stop and ask; do not auto-proceed.
  • Treat telemetry consent the same way as other explicit approval gates: if the user has not chosen yes or no, stop and ask instead of making the decision for them.
  • A broad request such as "full workflow", "全流程", "end-to-end", or "continue all the way" is scope authorization only. It does not count as checkpoint approval.
  • Never record checkpoint approval on the user's behalf with confirm-page-groups --yes or confirm-schema --yes unless the user explicitly confirms that checkpoint in the current turn.
  • When live GTM containers are detected on the site, do not bypass the live baseline review before schema generation.
  • Do not bypass schema approval before generate-gtm unless the user explicitly wants --force.
  • Treat preview QA and publish as separate decisions.
  • Treat tracking-health.json as the publish gate; do not jump to publish when health is missing, manual-only, or blocked unless the user explicitly wants --force.
  • Treat Shopify manual verification as the expected path for Shopify runs, not as a fallback error case.
  • Treat tracking_health_audit as an audit-only workflow mode. Do not run GTM deployment actions (generate-gtm, sync, publish) unless the user explicitly asks to override.

Resume And Closeout

When resuming:

  • prefer workflow-state.json when present
  • still inspect the real artifact set if warnings indicate stale gates
  • use status when the next step is unclear

When a phase or the full workflow ends, keep the closeout answer-first:

  • lead with a compact, decision-ready summary in plain language
  • do not dump raw JSON, raw URL lists, or artifact inventory before the summary
  • list files, checkpoint, and next command only after the human-readable summary

References

© jtrackingai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 114 other files (scripts, references) in the repository root of jtrackingai/analytics-tracking-automation.

  • SKILL.md
  • .github/ISSUE_TEMPLATE/bug_report.md
  • .github/ISSUE_TEMPLATE/config.yml
  • .github/ISSUE_TEMPLATE/feature_request.md
  • .github/ISSUE_TEMPLATE/site_compatibility.md
  • .gitignore
  • ARCHITECTURE.md
  • CONTRIBUTING.md
  • DEVELOPING.md
  • LICENSE
  • README.md
  • VERSION
  • agents/openai.yaml
  • docs/README.install.md
  • docs/assets/.gitkeep
  • docs/assets/jtracking-social-preview.png
  • … and 99 more

Open the folder on GitHubat commit 68378e0

Compare with similar skills

Analytics Tracking Automation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Analytics Tracking Automation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Analytics Tracking Automation this skilljtrackingai/analytics-tracking-automation142—~2.8kAutomated safety check: PassApache-2.0
13 Data Analysis Globalminhnv0807/ai-business-skills610—~4kAutomated safety check: PassMIT
Gtm Tracking Plancognyai/claude-code-marketing-skills104—~1.4kAutomated safety check: NotesNone
Analytics Trackingborghei/Claude-Skills886—~5.7kAutomated safety check: PassMIT
Analytics Trackingfreekmurze/dotfiles1k12 repos~2kAutomated safety check: PassNone
Gtm Setupcognyai/claude-code-marketing-skills104—~4.8kAutomated safety check: NotesNone

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More from jtrackingai/analytics-tracking-automation

All 8 skills in this repo

  • Tracking Discover

    jtrackingai/analytics-tracking-automation

    A skill your agent uses when the user wants crawl coverage, platform detection, dataLayer discovery, or a fresh artifact directory before grouping and schema work.

    142 GitHub stars~614 tokensUpdated 5 mo ago
    Auto-check passed

  • Tracking Group

    jtrackingai/analytics-tracking-automation

    A skill your agent uses when the work starts from site-analysis.json and the user wants page-group authoring, grouping adjustments, or page-group approval.

    142 GitHub stars~492 tokensUpdated 5 mo ago
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  • Tracking Live Gtm

    jtrackingai/analytics-tracking-automation

    A skill your agent uses when the user wants to inspect the real live GTM runtime before schema generation or compare multiple live GTM containers.

    142 GitHub stars~721 tokensUpdated 5 mo ago
    Auto-check passed

  • Tracking Schema

    jtrackingai/analytics-tracking-automation

    A skill your agent uses when the user wants schema preparation, event design, selector validation, schema review, or event-spec generation.

    142 GitHub stars~1.1k tokensUpdated 5 mo ago
    Auto-check passed

  • Tracking Sync

    jtrackingai/analytics-tracking-automation

    A skill your agent uses when the user wants GTM-ready config generation, GTM workspace sync, or container selection from an approved schema.

    142 GitHub stars~677 tokensUpdated 5 mo ago
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  • Tracking Verify

    jtrackingai/analytics-tracking-automation

    A skill your agent uses when the user wants preview QA, failure interpretation, release readiness, or an explicit publish handoff.

    142 GitHub stars~695 tokensUpdated 5 mo ago
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Works with

Categories

Questions about Analytics Tracking Automation

What does Analytics Tracking Automation do?

A skill your agent uses when you need GA4 + GTM tracking delivery from site discovery through publish, or when the right phase entry point is still unclear. Analytics Tracking Automation is an agent skill from jtrackingai/analytics-tracking-automation. Use when you need GA4 + GTM tracking delivery from site discovery through publish, or when the right phase entry point is still unclear.

When should I use Analytics Tracking Automation?

Analytics Tracking Automation fits situations like: you need GA4 + GTM tracking delivery from site discovery through publish; the right phase entry point is still unclear.

How do I install Analytics Tracking Automation in Claude Code?

Run `npx skills add jtrackingai/analytics-tracking-automation --skill analytics-tracking-automation -a claude-code`. Or copy the skill folder (the jtrackingai/analytics-tracking-automation repository) into .claude/skills/analytics-tracking-automation in your project. Claude Code loads it when a task matches its description.

How do I install Analytics Tracking Automation in Codex?

Run `npx skills add jtrackingai/analytics-tracking-automation --skill analytics-tracking-automation -a codex`. Or copy the skill folder (the jtrackingai/analytics-tracking-automation repository) into .agents/skills/analytics-tracking-automation in your project. Codex loads it when a task matches its description.

Can I use Analytics Tracking Automation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jtrackingai/analytics-tracking-automation --skill analytics-tracking-automation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analytics-tracking-automation, .gemini/skills/analytics-tracking-automation, .github/skills/analytics-tracking-automation and .opencode/skills/analytics-tracking-automation in your project.

What does Analytics Tracking Automation need to run?

Going by SKILL.md and its folder, Analytics Tracking Automation needs the command-line tools its instructions call (node, npm and npx). Our summary lists: Node.js. Compatibility (from SKILL.md): Requires Node.js 18+, npm, and Playwright Chromium for browser-backed steps. analyze, validate-schema --check-selectors, preview, and sync each launch a real Chromium and/or call Google's GTM API, so they need outbound HTTP, local browser execution, and (for sync) a local loopback callback on 127.0.0.1 to receive Google's OAuth consent redirect. Run them in an environment that provides those capabilities. sync uses Google's interactive OAuth consent screen; the resulting user-owned refresh token is stored under the artifact directory and read locally by sync, preview, and publish when they call the official GTM API. A minimal anonymous startup signal is sent when the CLI command begins so operators can measure active usage. Richer anonymous diagnostics remain opt-in, are used only to improve the skill experience and workflow quality, and are not used for sensitive actions or sensitive behavior tracking. .

Does Analytics Tracking Automation access the network?

SKILL.md contains no URLs. Its commands use npm and npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Analytics Tracking Automation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Analytics Tracking Automation use?

Analytics Tracking Automation is published under the Apache-2.0 licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Analytics Tracking Automation use?

About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 18k tokens, read only when the agent opens those files.

What are the alternatives to Analytics Tracking Automation?

Skills that share tags, products or a category with Analytics Tracking Automation: 13 Data Analysis Global (minhnv0807/ai-business-skills, 610 stars), Gtm Tracking Plan (cognyai/claude-code-marketing-skills, 104 stars), Analytics Tracking (borghei/Claude-Skills, 886 stars) and Analytics Tracking (freekmurze/dotfiles, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Analytics Tracking Automation?

jtrackingai (a GitHub user) maintains it in jtrackingai/analytics-tracking-automation, which has 142 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on April 29, 2026.

Source: jtrackingai/analytics-tracking-automation on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.