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.

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.

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.

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

• skill-map.md for the umbrella / phase skill map
• architecture.md for lifecycle, checkpoints, and resume semantics
• output-contract.md for artifact files and gate semantics
• shopify-workflow.md for Shopify-specific branch expectations
• telemetry-consent.md for the telemetry consent gate wording and behavior contract

Analytics Tracking Automation

analytics-tracking-automation is a local-first AI skill for planning, reviewing, and delivering GA4 + GTM tracking.

Use it when you want an agent to help with:

• analyzing a site before tracking work starts
• grouping pages by business purpose
• designing or reviewing a GA4 event plan
• comparing a proposed plan with an existing live GTM setup
• preparing GTM-ready outputs and verification guidance
• handling both generic websites and Shopify storefronts

This README is intentionally user-facing and conversation-first. If you need the CLI surface or maintainer workflow, use DEVELOPING.md.

What You Get

For a given website, this skill can help produce:

• a reviewable site analysis
• business-friendly page groups
• a compact, decision-ready tracking plan
• GTM-ready tracking outputs
• verification and health summaries before go-live
• artifact-backed progress that can be resumed later

Installation

Most users only need the umbrella skill.

Recommended

Clone the repository locally, then install the skill into your agent skills directory:

git clone https://github.com/jtrackingai/analytics-tracking-automation.git
cd analytics-tracking-automation
npm run install:skills

No-Clone Alternative

If you do not want to clone the repository, install the root skill directly:

npx skills add jtrackingai/analytics-tracking-automation

For advanced install options and exported skill bundles:

• docs/README.install.md
• docs/skills.md

ClawHub Publish

If you are publishing this skill to ClawHub, publish the exported public bundle instead of the full repository:

npm run export:skills:clawhub

Then upload dist/clawhub-skill-bundles/analytics-tracking-automation.

That public bundle is a publish-safe skill bundle. It keeps the agent-facing skill docs and references while stripping bundled executable runtime files (CLI bootstrap, packaged node modules, telemetry transport, and updater runtime) that tend to trigger stricter marketplace security scans.

When users install/use this public ClawHub bundle, they must run this prerequisite first (before any event-tracking command):

npx skills add jtrackingai/analytics-tracking-automation

Quick Start

Use It As A Skill

The intended experience is simple: tell your agent what you want in plain language.

Good requests usually include one or more of:

• the site URL
• whether this is a new setup, update, upkeep, or audit
• the output root for a new site run, such as ./output or /tmp/output
• an existing site artifact directory if you already have one, such as ./output/example_com
• GA4 measurement ID or GTM context when you already know them
• any scope boundary such as "stop after schema review"

For a new setup, the output root is not the artifact directory itself. The agent/CLI creates one artifact directory per site under that root, for example ./output/example_com.

Example Prompts

New setup from scratch:

Use analytics-tracking-automation to plan GA4 + GTM tracking for https://www.example.com.
Use ./output as the output root; create the site artifact directory under it.
Start from a fresh run and stop after the event schema is ready for review.

New setup with implementation context:

Use analytics-tracking-automation to set up tracking for https://www.example.com.
Use /tmp/output as the output root, so this site's artifacts go under /tmp/output/www_example_com.
GA4 Measurement ID is G-XXXXXXXXXX.
We care most about signup, pricing, contact, and demo intent.

Audit only:

Use analytics-tracking-automation to run a tracking health audit for https://www.example.com.
I only want to understand the current live GTM setup and whether we should repair or rebuild.
Do not continue into deployment work.

Routine upkeep:

Use analytics-tracking-automation to do an upkeep review for this existing run:
./output/example_com
Tell me what is still healthy, what drifted, and what needs repair.

Update an existing artifact:

Use analytics-tracking-automation to resume this artifact directory:
./output/example_com
Tell me the current checkpoint and continue only through schema review.

Page-group review only:

Use analytics-tracking-automation to review and refine the page groups in:
./output/example_com/site-analysis.json
Focus on business intent, not just URL shape.

Shopify branch:

Use analytics-tracking-automation for this Shopify storefront:
https://store.example.com
I want the Shopify-specific tracking path, not the generic website flow.

How To Think About It

This skill is best when you want the agent to act like a tracking lead, not just a command runner.

A typical conversation flow is:

1. inspect the site or resume an existing run
2. group pages in a reviewable way
3. draft or revise the event plan
4. review what should be reused, repaired, added, or dropped
5. continue into GTM generation and verification only when you explicitly want that

Where To Go Next

• Installation details: docs/README.install.md
• Skill family map: docs/skills.md
• Agent-facing workflow contract: SKILL.md
• CLI and maintainer workflow: DEVELOPING.md

Quick Debug Tips

If preview troubleshooting points to selector mismatch or page-load/navigation issues, these Playwright CLI helpers are faster than repeatedly re-running the full flow:

npm run debug:open -- https://www.example.com
npm run debug:codegen -- https://www.example.com

• debug:open: headed browser for quick visual checks (redirect loops, WAF pages, blocked content).
• debug:codegen: interactive selector capture for fixing event-schema.json selectors.

Product Boundary

• the workflow runs locally
• browser-backed steps rely on Playwright Chromium; npm install triggers the package postinstall step that installs the browser binary
• GTM sync uses Google OAuth
• OAuth credentials are cached in the artifact directory for the current site run
• generic sites use automated preview verification
• Shopify uses the Shopify-specific branch and manual post-install validation
• a minimal anonymous startup signal is sent when an event-tracking command begins so operators can measure active usage; it is session-scoped and limited to technical metadata such as command name, CLI version, OS family, Node major version, and a per-invocation session identifier
• richer anonymous usage diagnostics remain opt-in and the first explicit choice is stored in local user config; if enabled, future runs send higher-level workflow data such as command name, success/failure status, rough counts, site hostname, detected platform, and broad workflow checkpoints so operators can improve the product and troubleshoot reliability; if declined, future runs continue normally without these richer diagnostics until the user changes that local config choice; those richer diagnostics do not send full URLs, page paths, query strings, file paths, GTM/GA IDs, selectors, OAuth data, raw errors, or page content; the remaining privacy risk is that the site hostname and workflow metadata still reveal which domain was worked on and broad usage patterns; if a workflow prompt asks for telemetry consent and no stored preference exists, the operator must stop and let the user choose yes or no instead of answering on the user's behalf
• installed copy bundles can self-check GitHub for updates and reinstall the same selected bundle set

Need A More Advanced Setup?

This skill reflects the implementation workflow behind JTracking.

If you need a more advanced setup, JTracking also supports:

• richer tracking design based on concrete business flows
• server-side tracking and custom loaders
• more destination and ad-platform integrations
• longer-term tracking operations and maintenance

Contact Us

If you run into any issues while using this skill, contact us at support@jtracking.ai.

We will reply as soon as we see your message.

License

This project is licensed under the Apache License, Version 2.0. See LICENSE for the full text.

Use of the JTracking name, logo, and other brand assets is not granted under this license.