Tracking Verify

Community

jtrackingai

tracking-verify

Use when the user wants preview QA, failure interpretation, release readiness, or an explicit publish handoff.

Overview

Publisher	jtrackingai
Repository	`analytics-tracking-automation`
Skill name	`tracking-verify`
Stars	140
Forks	39
Bundled files	1
License	Apache-2.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by jtrackingai on GitHub. Read the source before you install it.

Installation

Install the Tracking Verify AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/jtrackingai/analytics-tracking-automation/tree/main/skills/tracking-verify

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/jtrackingai/analytics-tracking-automation.git /tmp/analytics-tracking-automation
mkdir -p .claude/skills
cp -r /tmp/analytics-tracking-automation/skills/tracking-verify .claude/skills/tracking-verify

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tracking Verify in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Tracking Verify on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Tracking Verify is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Tracking Verify

Use this skill for verification and optional publish handoff.

Inputs

<artifact-dir>/event-schema.json
<artifact-dir>/gtm-context.json

Workflow

If the telemetry consent prompt appears and no prior choice is recorded, stop and follow ../../references/telemetry-consent.md before continuing.

Run preview:

bash
./event-tracking preview <artifact-dir>/event-schema.json --context-file <artifact-dir>/gtm-context.json

If comparing against an older preview run, pass the previous health baseline:

bash
./event-tracking preview <artifact-dir>/event-schema.json --context-file <artifact-dir>/gtm-context.json --baseline <previous-tracking-health.json>

preview launches a real Chromium via Playwright and exercises the live site to fire GA4/GTM events for verification. Run it in an environment that permits outbound network and local browser execution; environments that restrict either tend to cause Playwright to hang or fail silently rather than return a clean error.

Then interpret:

blockers
expected failures
selector mismatches
unexpected fired events outside the approved schema
release readiness

If the user explicitly wants to publish after verification:

bash
./event-tracking publish --context-file <artifact-dir>/gtm-context.json --version-name "GA4 Events v1 - <date>"

If tracking-health.json is missing, still manual-only, or has blockers, publish now stops by default. Only use --force when the user explicitly wants to override that gate.

Required Output

Produce and share:

<artifact-dir>/preview-report.md
<artifact-dir>/preview-result.json
<artifact-dir>/tracking-health.json
<artifact-dir>/tracking-health-report.md
<artifact-dir>/tracking-health-history/
updated <artifact-dir>/workflow-state.json

Closeout Style

default to a verification verdict first: healthy, blocked, or manual follow-up required
summarize blockers, unexpected events, and release-readiness in plain language before listing files
keep raw preview data and artifact references after the summary

Stop Boundary

stop after preview if the user only asked for QA
publish only when the user explicitly wants to affect the live site

If the platform is Shopify, switch to the Shopify-specific rules in tracking-shopify.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

agents/openai.yaml1 KB

Frequently asked questions

What does the Tracking Verify AI skill do?

Use when the user wants preview QA, failure interpretation, release readiness, or an explicit publish handoff.

Why use Tracking Verify on TypingMind?

Because you install it once and use it with any model. Tracking Verify is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Tracking Verify in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jtrackingai/analytics-tracking-automation/tree/main/skills/tracking-verify. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Tracking Verify?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Tracking Verify?

As many as you like. As long as a model supports skills, you can use Tracking Verify with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Tracking Verify AI skill free?

Yes. It is published on GitHub by jtrackingai under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Tracking Verify

Inputs

Workflow

Required Output

Closeout Style

Stop Boundary

References

Bundled files

Frequently asked questions

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