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Tracking Setup (Global) · minhnv0807 | DecimalAI

Marketingby minhnv0807

Tracking Setup (Global)

Use when the user needs to set up or fix conversion tracking before running ads: Meta Pixel and Conversions API, Google Ads conversion tracking with Enhanced Conversions, GA4, TikTok Pixel and Events API, server-side GTM, consent management for GDPR and CCPA, UTM conventions, iOS ATT attribution windows, and the pre-launch verification checklist. Trigger on 'tracking setup', 'pixel setup', 'conversions API', 'CAPI', 'GA4 setup', 'server-side tracking', 'consent mode', 'UTM convention', or 'conve

Maintained

SkillScore

SkillScore77/100

Test results 77

Safety

3/3 safety checks passed

Code scan
Intent
Content

What it changes

55%77%of test cases passed +23 pts

Without skill12 of 22

With skill17 of 22

8 fixed9 passed either way2 still failing3 broke

Measured on gemini-3.6-flash9/2/2026v1 · latest is v2

This benchmark measured an earlier version of the skill.

Track record

Agent runs: 0; All time

See one task, with and without the skill

One test taskWe are documenting tracking setup for a SaaS client product named 'Acme CRM' on October 15, 2026. Specify the required document output filename convention and the exact metadata header structure required at the top of the file.

Without the skillMissed

With the skillPassed

Same model, same task. Answers are capped and redacted.

Use this skill

Your agent runs on

Adds every file the skill has, pinned so you can update it. No account needed.

pip install "decimalai>=0.15"
decimalai skills add minhnv0807-53-tracking-setup-global
claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"

The same install from Python, for a notebook or a setup script.

Install

pip install "decimalai>=0.15"

Add the skill

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

print("Added. Start Claude Code with the command below.")

Start Claude Code with it

claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"

Type these in a Claude Code session. No account or API key. It writes the skill and any files it bundles, and asks first when its safety rating isn't Passed.

Add the DecimalAI plugin, once

/plugin marketplace add decimal-labs/decimalai-claude-plugins
/plugin install decimalai@decimalai

Install this skill

/decimalai:install minhnv0807-53-tracking-setup-global

The plugin needs python3 and curl on your machine.

No Python or account. Claude Code picks it up in its next session.

Save it into your project

curl -fsSL --create-dirs -o .claude/skills/minhnv0807-53-tracking-setup-global/SKILL.md https://app.decimal.ai/s/minhnv0807-53-tracking-setup-global/SKILL.md

Copy SKILL.md

Save it in your project, as

.claude/skills/minhnv0807-53-tracking-setup-global/SKILL.md

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Claude Code docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"
decimalai skills add minhnv0807-53-tracking-setup-global

Add it to your agent

import asyncio

from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

async def main():
    question = "Hello!"
    async with support.run(question) as run:  # one user message, one run
        async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
            print(message)

# In a notebook or async code: await main()
asyncio.run(main())

Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[claude-agent-sdk]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

import asyncio

from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

async def main():
    question = "Hello!"
    async with support.run(question) as run:  # one user message, one run
        async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
            print(message)

# In a notebook or async code: await main()
asyncio.run(main())

Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from claude_agent_sdk import ClaudeAgentOptions, query

skill = Path(".agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md").read_text()
options = ClaudeAgentOptions(system_prompt=f"You are a helpful agent.\n\n{skill}", max_turns=6)

async def main():
    async for message in query(prompt="Hello!", options=options):
        print(message)

# In a notebook or async code: await main()
asyncio.run(main())

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Claude Agent SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai-agents]"
decimalai skills add minhnv0807-53-tracking-setup-global

Add it to your agent

from agents import Agent, Runner
from decimalai.openai_agents import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    name=support.name,
    instructions=support.instructions,  # your prompt, then the skill list
    tools=[*support.tools],             # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.

Install

pip install "decimalai[openai-agents]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

from agents import Agent, Runner
from decimalai.openai_agents import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    name=support.name,
    instructions=support.instructions,  # your prompt, then the skill list
    tools=[*support.tools],             # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

Give it to your agent

from pathlib import Path
from agents import Agent, Runner

skill = Path(".agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md").read_text()
agent = Agent(name="support", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

OpenAI Agents docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[openai]"
decimalai skills add minhnv0807-53-tracking-setup-global

Add it to your agent

import json

from openai import OpenAI
from decimalai.openai import agent_config

client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
                   "required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    # run.system is your prompt, then the skill list.
    messages = [{"role": "system", "content": run.system}, run.message]
    while True:
        reply = client.chat.completions.create(
            model="gpt-5.4-mini",
            messages=messages,
            tools=[*TOOLS, *run.tools],  # your tools, then load_skill
        ).choices[0].message
        messages.append(reply)
        if not reply.tool_calls:
            break
        for call in reply.tool_calls:
            # load_skill is answered by the run; your own tools by FUNCTIONS.
            function = FUNCTIONS.get(call.function.name)
            messages.append(run.tool_result(call) or {
                "role": "tool", "tool_call_id": call.id,
                "content": function(**json.loads(call.function.arguments)) if function
                else f"There is no tool named {call.function.name!r}.",
            })
print(reply.content)

# The Responses API takes run.response_tools instead of run.tools.

Install

pip install "decimalai[openai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

import json

from openai import OpenAI
from decimalai.openai import agent_config

client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
                   "required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    # run.system is your prompt, then the skill list.
    messages = [{"role": "system", "content": run.system}, run.message]
    while True:
        reply = client.chat.completions.create(
            model="gpt-5.4-mini",
            messages=messages,
            tools=[*TOOLS, *run.tools],  # your tools, then load_skill
        ).choices[0].message
        messages.append(reply)
        if not reply.tool_calls:
            break
        for call in reply.tool_calls:
            # load_skill is answered by the run; your own tools by FUNCTIONS.
            function = FUNCTIONS.get(call.function.name)
            messages.append(run.tool_result(call) or {
                "role": "tool", "tool_call_id": call.id,
                "content": function(**json.loads(call.function.arguments)) if function
                else f"There is no tool named {call.function.name!r}.",
            })
print(reply.content)

# The Responses API takes run.response_tools instead of run.tools.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

Give it to your agent

from pathlib import Path
from openai import OpenAI

client = OpenAI()
skill = Path(".agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md").read_text()
reply = client.chat.completions.create(
    model="gpt-5.4-mini",
    messages=[
        {"role": "system", "content": f"You are a helpful agent.\n\n{skill}"},
        {"role": "user", "content": "Hello!"},
    ],
).choices[0].message

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

OpenAI SDK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[anthropic]"
decimalai skills add minhnv0807-53-tracking-setup-global

Add it to your agent

import anthropic
from decimalai.anthropic import agent_config

client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

question = "Hello!"
with support.run(question) as run:  # one user message, one run
    answer = client.beta.messages.tool_runner(
        model="claude-haiku-5-5",
        max_tokens=4096,
        system=run.system,     # your prompt, then the skill list
        tools=[*run.tools],    # your tools, then load_skill
        messages=[{"role": "user", "content": question}],
    ).until_done()

Install

pip install "decimalai[anthropic]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

import anthropic
from decimalai.anthropic import agent_config

client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

question = "Hello!"
with support.run(question) as run:  # one user message, one run
    answer = client.beta.messages.tool_runner(
        model="claude-haiku-5-5",
        max_tokens=4096,
        system=run.system,     # your prompt, then the skill list
        tools=[*run.tools],    # your tools, then load_skill
        messages=[{"role": "user", "content": question}],
    ).until_done()

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

Give it to your agent

from pathlib import Path
import anthropic

client = anthropic.Anthropic()
skill = Path(".agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md").read_text()
reply = client.messages.create(
    model="claude-haiku-5-5",
    max_tokens=4096,
    system=f"You are a helpful agent.\n\n{skill}",
    messages=[{"role": "user", "content": "Hello!"}],
)

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Anthropic docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[google-genai]"
decimalai skills add minhnv0807-53-tracking-setup-global

Add it to your agent

from google import genai
from google.genai import types
from decimalai.google_genai import agent_config

client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
                               "required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    config = types.GenerateContentConfig(
        system_instruction=run.system,     # your prompt, then the skill list
        tools=[*TOOLS, *run.tool_params],  # your functions, then load_skill
    )
    contents = [{"role": "user", "parts": [{"text": run.message}]}]
    while True:
        response = client.models.generate_content(
            model="gemini-3.5-flash", contents=contents, config=config,
        )
        if not response.function_calls:
            break
        contents.append(response.candidates[0].content)
        parts = []
        for call in response.function_calls:
            # load_skill is answered by the run; your own functions by FUNCTIONS.
            # A loop of your own rather than automatic function calling, which
            # raises KeyError when the model asks for a function you did not pass.
            function = FUNCTIONS.get(call.name)
            parts.append(run.tool_result(call) or {"function_response": {
                "name": call.name, "id": call.id,
                "response": {"result": function(**(call.args or {})) if function
                             else f"There is no function named {call.name!r}."},
            }})
        contents.append({"role": "user", "parts": parts})
print(response.text)

Install

pip install "decimalai[google-genai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

from google import genai
from google.genai import types
from decimalai.google_genai import agent_config

client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")


def lookup_order(order_id: str) -> str:
    return f"Order {order_id} shipped yesterday."


# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
    "name": "lookup_order",
    "description": "Look up the status of an order.",
    "parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
                               "required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}

question = "Where is order A1001?"
with support.run(question) as run:  # one user message, one run
    config = types.GenerateContentConfig(
        system_instruction=run.system,     # your prompt, then the skill list
        tools=[*TOOLS, *run.tool_params],  # your functions, then load_skill
    )
    contents = [{"role": "user", "parts": [{"text": run.message}]}]
    while True:
        response = client.models.generate_content(
            model="gemini-3.5-flash", contents=contents, config=config,
        )
        if not response.function_calls:
            break
        contents.append(response.candidates[0].content)
        parts = []
        for call in response.function_calls:
            # load_skill is answered by the run; your own functions by FUNCTIONS.
            # A loop of your own rather than automatic function calling, which
            # raises KeyError when the model asks for a function you did not pass.
            function = FUNCTIONS.get(call.name)
            parts.append(run.tool_result(call) or {"function_response": {
                "name": call.name, "id": call.id,
                "response": {"result": function(**(call.args or {})) if function
                             else f"There is no function named {call.name!r}."},
            }})
        contents.append({"role": "user", "parts": parts})
print(response.text)

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

Give it to your agent

from pathlib import Path
from google import genai
from google.genai import types

client = genai.Client()
skill = Path(".agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md").read_text()
response = client.models.generate_content(
    model="gemini-3.5-flash",
    contents="Hello!",
    config=types.GenerateContentConfig(system_instruction=f"You are a helpful agent.\n\n{skill}"),
)

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Gemini API docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[langchain]" langchain-openai
decimalai skills add minhnv0807-53-tracking-setup-global

Add it to your agent

from langchain.agents import create_agent
from decimalai.langchain import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = create_agent(
    "openai:gpt-5.4-mini",
    tools=[],                         # your tools; the middleware adds load_skill
    middleware=[support.middleware],  # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

Install

pip install "decimalai[langchain]" langchain-openai

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

from langchain.agents import create_agent
from decimalai.langchain import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = create_agent(
    "openai:gpt-5.4-mini",
    tools=[],                         # your tools; the middleware adds load_skill
    middleware=[support.middleware],  # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

Give it to your agent

from pathlib import Path
from langchain.agents import create_agent

skill = Path(".agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md").read_text()
agent = create_agent("openai:gpt-5.4-mini", tools=[], system_prompt=f"You are a helpful agent.\n\n{skill}")
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

LangChain docs

CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"
decimalai skills add minhnv0807-53-tracking-setup-global

Add it to your agent

import decimalai.crewai
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                               # your own CrewAI LLM
    skills=decimalai.crewai.skills(),      # the installed folder
    tools=decimalai.crewai.skill_tools(),  # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

The same install from Python, for a notebook or a setup script. CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" "crewai>=1.15.27"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

import decimalai.crewai
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                               # your own CrewAI LLM
    skills=decimalai.crewai.skills(),      # the installed folder
    tools=decimalai.crewai.skill_tools(),  # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

No DecimalAI package. CrewAI's own loader reads the folder, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

Give it to your agent

from pathlib import Path
from crewai import Agent, Crew, Task

agent = Agent(
    role="Support", goal="Help the customer", backstory="A support agent.",
    llm=llm,                         # your own CrewAI LLM
    skills=[Path(".agents/skills")],
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

CrewAI docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[adk]"
decimalai skills add minhnv0807-53-tracking-setup-global

Add it to your agent

from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = LlmAgent(
    name="support",          # ADK needs a Python identifier
    model="gemini-3.5-flash",
    instruction=support.instruction,  # your prompt, then the skill list
    tools=[*support.tools],           # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])

Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

Install

pip install "decimalai[adk]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = LlmAgent(
    name="support",          # ADK needs a Python identifier
    model="gemini-3.5-flash",
    instruction=support.instruction,  # your prompt, then the skill list
    tools=[*support.tools],           # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])

Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

Give it to your agent

from pathlib import Path
from google.adk.agents import LlmAgent

skill = Path(".agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md").read_text()
agent = LlmAgent(
    name="support",
    model="gemini-3.5-flash",
    instruction=lambda context: f"You are a helpful agent.\n\n{skill}",
)

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Google ADK docs

agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.

Install

pip install "decimalai[pydantic-ai]"
decimalai skills add minhnv0807-53-tracking-setup-global

Add it to your agent

from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    "openai:gpt-4o-mini",
    name=support.name,
    tools=[],                 # your tools; the capability adds load_skill
    capabilities=[support],   # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.

Install

pip install "decimalai[pydantic-ai]"

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config

# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")

agent = Agent(
    "openai:gpt-4o-mini",
    name=support.name,
    tools=[],                 # your tools; the capability adds load_skill
    capabilities=[support],   # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

Give it to your agent

from pathlib import Path
from pydantic_ai import Agent

skill = Path(".agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md").read_text()
agent = Agent("openai:gpt-4o-mini", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Pydantic AI docs

Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents
decimalai skills add minhnv0807-53-tracking-setup-global

Add it to your agent

import decimalai.deepagents
from deepagents import create_deep_agent

agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).

The same install from Python, for a notebook or a setup script. Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" deepagents

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

import decimalai.deepagents
from deepagents import create_deep_agent

agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

Give it to your agent

from pathlib import Path
from deepagents import create_deep_agent

skill = Path(".agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md").read_text()
agent = create_deep_agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Deep Agents docs

Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework
decimalai skills add minhnv0807-53-tracking-setup-global

Add it to your agent

import asyncio

from agent_framework import Agent
from decimalai.agent_framework import skills

agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))

It caches skills by default, so restart the process after decimalai skills update.

The same install from Python, for a notebook or a setup script. Its own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" agent-framework

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

import asyncio

from agent_framework import Agent
from decimalai.agent_framework import skills

agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))

It caches skills by default, so restart the process after decimalai skills update.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

Give it to your agent

import asyncio
from pathlib import Path
from agent_framework import Agent

skill = Path(".agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md").read_text()
agent = Agent(client=client, instructions=f"You are a helpful agent.\n\n{skill}")
asyncio.run(agent.run("Hello!"))

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Microsoft Agent Framework docs

Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents
decimalai skills add minhnv0807-53-tracking-setup-global

Add it to your agent

from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell

agent = Agent(
    model=model,                # always pass one: the default is Amazon Bedrock
    system_prompt="You are a helpful agent.",
    tools=[file_editor, shell],
    plugins=[skills()],
)
agent("Hello!")

Strands loads an agent's skills once, so build the agent again after decimalai skills update.

The same install from Python, for a notebook or a setup script. Strands' own skill loader reads the installed folder. No DecimalAI account needed.

Install

pip install "decimalai>=0.16" strands-agents

Add it to your agent

from decimalai import skillpkg

# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("minhnv0807-53-tracking-setup-global")
if result.exit_code:
    raise SystemExit(result.problems)

from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell

agent = Agent(
    model=model,                # always pass one: the default is Amazon Bedrock
    system_prompt="You are a helpful agent.",
    tools=[file_editor, shell],
    plugins=[skills()],
)
agent("Hello!")

Strands loads an agent's skills once, so build the agent again after decimalai skills update.

No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

Give it to your agent

from pathlib import Path
from strands import Agent

skill = Path(".agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md").read_text()
agent = Agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent("Hello!")

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Strands docs

Adds every file the skill has, pinned so you can update it. Cursor, Copilot, Cline and Warp read this folder by themselves.

pip install "decimalai>=0.15"
decimalai skills add minhnv0807-53-tracking-setup-global

No Python or account. Cursor, Copilot, Cline and Warp read this folder by themselves.

Save it into your project

curl -fsSL --create-dirs -o .agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md https://app.decimal.ai/s/minhnv0807-53-tracking-setup-global/SKILL.md

Copy SKILL.md

Save it in your project, as

.agents/skills/minhnv0807-53-tracking-setup-global/SKILL.md

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Cursor and other editors docs

Fetch the file and give its text to your model as instructions. No account or package needed.

Get the file

curl -fsSL https://app.decimal.ai/s/minhnv0807-53-tracking-setup-global/SKILL.md

Read the summary as JSON

curl -fsSL https://app.decimal.ai/s/minhnv0807-53-tracking-setup-global.json

This gets SKILL.md only. The skill's 1 other file is not included.

Other ways to add it

Other setups docs

You don't need a DecimalAI account.

Version: v2 (v1 tested 9/2/2026)
Source: minhnv0807/ai-business-skills ↗
License: MIT

Manage it in DecimalAI

Saved prompts and skills, pinned versions, and traces of this skill in your runs. DecimalAI does not run your agent.

Claude Code reads files from your project, so DecimalAI config does not apply there.

On Claude Agent SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI Agents: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On OpenAI SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Anthropic: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Gemini API: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On LangChain: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On CrewAI: set DECIMAL_API_KEY and add decimalai.init(crewai=True) to record runs and skill use. The skill version stays in your repo.

On Google ADK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Pydantic AI: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.

On Deep Agents: set DECIMAL_API_KEY and add decimalai.init(langchain=True) to record runs and skill use. The skill version stays in your repo.

On Microsoft Agent Framework: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

On Strands: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.

Editors read files from your project, so DecimalAI config does not apply there.

Anywhere else: record a use with decimalai.log_skill_activation() inside a trace.

Use this skill

SKILL.md

Tracking Setup (Global)

Operating rules: skills/en/references/operating-rules-global.md (esp. rules 2, 3, 7).

Ads without verified tracking is driving blind. Hard rule: do not launch ads until tracking verifies green. Every dollar spent before verification is unmeasurable. Set it up correctly the first time — changing events mid-campaign destroys historical comparability.

Full per-platform install steps and the consent mode parameter reference: read references/platform-tracking-setup.md.

Information gathering

Ask up to 4 questions:

Which ad platforms and objective? Meta / Google / TikTok / LinkedIn / YouTube — lead (form or message) / purchase / traffic?
What runs the website or landing page? Shopify / WordPress / Webflow / Framer / custom — and is there access to edit the head tag or install GTM?
Which markets receive traffic? This decides the consent requirements: EU/UK means GDPR and ePrivacy, California means CCPA/CPRA, other US states have their own opt-out laws.
Where does the sale actually close? On site (pixel-measurable) or offline via sales calls, demos, or DMs (needs CRM/offline conversion import)?

Principles

No green, no launch. Verification comes before spend, every time.
Consent is part of tracking, not a legal afterthought. In the EU/UK, tags must not fire before consent. Getting this wrong risks fines and, on Google, loss of remarketing audiences.
One installation method only. GTM plus hardcoded tags equals duplicate events and doubled phantom conversions.
Client-side plus server-side, deduplicated. Browser-only tracking loses a large share of events to ad blockers, ITP, and iOS ATT. Send the same event from both sides with a shared event ID.
Consistent UTMs. Define the convention once, before anyone builds a link. GA4 cannot repair inconsistent casing or naming after the fact.
Measure to revenue, not to lead. If 1,000 leads produce 10 sales, you must be able to tell whether the failure is in ads or in sales. That requires CRM or offline conversion import.
Expect platform numbers to disagree. Ads managers use different attribution windows and modeled conversions. Pick one source of truth for decisions and use the others as directional.

Workflow

1. Choose the measurement architecture

Layer	Purpose	Minimum
Client-side pixel/tag	Fast setup, on-page events	Meta Pixel, Google tag, TikTok Pixel
Server-side API	Recovers events lost to blockers and ITP	Meta Conversions API, TikTok Events API, Google Enhanced Conversions
Analytics	Cross-channel truth, funnel analysis	GA4 with key events configured
Consent layer	Legal gate in front of everything above	CMP plus Google consent mode v2
CRM / offline	Connects leads to actual revenue	CRM with source fields, offline conversion import

Server-side GTM is the recommended container for anything beyond a simple store: it centralizes event forwarding, improves data quality, and keeps first-party cookie lifetimes usable under ITP.

2. Consent management (do this before any tag fires)

This is a first-class requirement, not an optional extra.

EU / UK — GDPR and ePrivacy:

Install a certified consent management platform. Meta requires a CMP for EU traffic; Google requires a Google-certified CMP for EEA/UK traffic to keep personalized advertising and audience features.
Implement Google consent mode v2. The four signals are ad_storage, analytics_storage, ad_user_data, ad_personalization. Default them to denied for EEA/UK before the banner is answered, then update on consent.
Non-essential tags must not fire before consent is granted. Consent must be as easy to refuse as to accept, and withdrawable.
Keep a consent log — which user, which choice, when, which policy version.

California — CCPA/CPRA (and comparable US state laws):

Provide a visible opt-out of sale/sharing of personal information.
Honor the Global Privacy Control browser signal as a valid opt-out.
On Meta, apply Limited Data Use for California traffic.

Email and SMS: CAN-SPAM in the US and GDPR in the EU require documented opt-in for marketing sends and a working unsubscribe. Any list uploaded as a Custom Audience or Customer Match list must have that consent on record — see 14-email-marketing-global.

Record the decision in the output file: which CMP, which regions gated, who verified.

Vietnam traffic: personal-data duties for Vietnamese visitors and customers are not covered here. See the VN legal hub skills/vi/references/phap-ly-marketing-vn.md section 2 and verify the source instruments on vbpl.vn / thuvienphapluat.vn.

Any change to live tags, pixel settings, consent configuration, or an audience upload is a write action: draft it as a change block (current / proposed / rollback / named approver), apply only after approval, read back, and log it (operating rule 7).

3. Install per platform

Full step-by-step checklists live in references/platform-tracking-setup.md. Summary of what must exist:

Platform	Client-side	Server-side	Verification tool
Meta	Pixel with standard events (PageView, ViewContent, AddToCart, Lead, Purchase)	Conversions API with `event_id` deduplication, Event Match Quality >= 6.0	Meta Pixel Helper, Test Events
Google Ads	Google tag / GTM conversion actions	Enhanced Conversions (hashed email/phone), consent mode v2	Tag Assistant, conversion diagnostics
GA4	GA4 tag, key events marked as conversions	Measurement Protocol or server-side GTM	GA4 DebugView, Realtime
TikTok	TikTok Pixel (ViewContent, AddToCart, SubmitForm, CompletePayment)	Events API with deduplication	TikTok Pixel Helper, Events diagnostics
LinkedIn	Insight Tag with conversion rules	Conversions API for CRM-side events	LinkedIn Insight Tag Helper

Only one primary conversion action per objective should be enabled for bidding. Extra enabled conversions inflate counts and confuse smart bidding.

4. iOS ATT and attribution windows

Since iOS 14.5, a large share of iOS users opt out of app tracking, so platform-reported conversions are partly modeled rather than observed.

Meta's post-ATT default is a 7-day click / 1-day view attribution window. Compare periods on the same window or the trend is meaningless.
Verify the domain and configure Aggregated Event Measurement with a prioritized list of up to 8 web events per domain. The event you optimize for must be ranked highest.
Expect ads manager conversions and GA4 last-click conversions to differ, often materially. Decide up front which one drives budget decisions.
Server-side events plus Enhanced Conversions and good Event Match Quality recover a meaningful share of the loss. This is the main reason server-side is no longer optional.
Third-party cookie deprecation compounds this. Prioritize first-party data collection — email capture, account creation, CRM — over pixel-only audience building.

5. UTM convention

https://domain.com/lp?utm_source=[source]&utm_medium=[medium]&utm_campaign=[campaign]&utm_content=[ad_name]

Parameter	Convention	Example
utm_source	meta / google / tiktok / linkedin / klaviyo	meta
utm_medium	paid_social / paid_search / display / email / organic	paid_social
utm_campaign	`[product]_[audience]_[market]_[MMYY]`	course-a_cold_us_0726
utm_content	`[creative-type]_[hook-type]_[version]` — matches the ad name	vid_pain_v1

Lowercase, no spaces, no special characters. utm_content must equal the ad name defined in 52-account-structure-global so ads manager and GA4 reconcile in both directions. Add utm_term only for search keywords.

6. GA4 event mapping

GA4 event	Trigger	Platform equivalent
page_view	All pages	PageView (Meta), ViewContent (TikTok)
view_item	Product or offer page	ViewContent (Meta)
add_to_cart	Cart add	AddToCart (Meta/TikTok)
begin_checkout	Checkout started	InitiateCheckout (Meta)
generate_lead	Form submit or qualified message	Lead (Meta), SubmitForm (TikTok), Conversion (Google)
purchase	Payment confirmed, with value and currency	Purchase (Meta/TikTok/Google)

Each action fires exactly one event. Mark the event that matches the ads objective as a key event in GA4. Always send value and currency on purchase — without them ROAS cannot be computed and multi-market revenue cannot be normalized.

7. CRM and offline conversions

Required whenever the sale closes off-site (B2B, high-ticket, coaching, agency, phone or DM sales):

Capture source on every lead. CRM fields: source, medium, campaign, ad content, GCLID or fbclid, timestamp, owner, stage, disqualification reason, closed revenue.
Import offline conversions weekly. Meta offline/CAPI conversions and Google Ads offline conversion import via GCLID or Enhanced Conversions for Leads. This teaches bidding from real revenue instead of raw lead count.
Reconcile monthly. Compare CRM lead count against ads manager lead count. A large gap (20% is a heuristic starting band, tune it per account) signals a tracking or attribution problem, not a sales problem.

Uploaded CRM data must be hashed and covered by consent.

8. Verify green before launch

All must pass. One missing item means do not launch:

9. Ongoing checks

Daily (2 minutes): events flowing in the last 24 hours on every platform; Google Ads conversions recording; GA4 showing paid sessions.

Weekly: server-side match rate healthy against your own baseline (house heuristic: 70% as a starting band, verify against the platform's current docs); no duplicate events; lead counts across ads manager, GA4, and CRM within your tuned gap band (house heuristic: start near 20%); every live link carries a correct UTM; consent banner still firing correctly after any site release.

Discrepancy triage

When ads manager, GA4, and backend numbers disagree, classify the gap before changing budgets or tags.

Source of truth first. Orders = backend order system; leads = CRM. Platform and GA4 figures are directional.
Compare like with like. Same date range, timezone, currency, and attribution window.
Expected causes (not defects): attribution window, click vs view-through, modeled conversions, timezone/currency, session vs user counting, ad blockers and consent declines, cross-device.
Double-sender check: pixel plus server API without a shared event_id double-counts; a GTM tag plus a hardcoded snippet duplicates; a platform plugin plus GTM duplicates. Keep one installation method.
Thank-you-page guard: fire the purchase or lead event once per order_id. Reloads, the back button, and bookmarked confirmation URLs all re-fire it, so dedupe server-side as well.
Test Events are not proof. A green Test Events panel only shows one test event arrived. Proof is one real order or lead traced end to end by its ID.
Label each finding observed / reported / inferred (operating rule 3). Missing data is unknown, not fail.
No universal percentage thresholds. Any "acceptable gap" band (for example 20%) is a heuristic to tune per account; record it as such.

Verdict per gap: expected / investigate / fix. The Vietnamese pack has a detailed reference and a reconciliation-report template (skills/vi/53-tracking-setup/references/chan-doan-lech-so-lieu.md); reuse its structure.

Troubleshooting

Problem	Common cause	Fix
Pixel does not fire	Tag missing on the page or blocked by consent gate	Check GTM preview and the consent state; confirm the tag is allowed after consent
Duplicate events	GTM and hardcoded tag both installed	Remove one; verify `event_id` deduplication
Low match rate / low EMQ	No hashed email or phone sent server-side	Add customer parameters to the server payload
Conversion not recorded	Wrong event name or wrong trigger page	Check spelling and that the trigger is the confirmation page
GA4 far below ads manager	Different attribution windows plus modeled conversions	Compare on the same window; treat one source as decision-grade
Remarketing audiences shrinking in the EU	Consent mode v2 missing or misconfigured	Implement all four consent signals and a certified CMP
Leads arrive with no source	No CRM source capture	Add hidden UTM/click-ID fields to every form

Output structure

File name: tracking-setup-[product]-[YYYYMMDD].md

# Tracking Setup — [Product/Campaign]
Platforms: [list] · Site platform: [x] · Markets: [x] · Objective: [Lead/Purchase]

## 1. Measurement architecture   [client, server, analytics, consent, CRM]
## 2. Consent plan               [CMP, regions gated, consent mode v2, LDU, log owner]
## 3. Platform setup status      [table with status per item]
## 4. Attribution settings       [window per platform, AEM priority list]
## 5. UTM convention             [parameters and real project examples]
## 6. Event mapping              [GA4 to platform events]
## 7. CRM / offline conversions  [fields captured, import cadence]
## 8. Pre-launch verification    [green checklist, verified by, date]
## 9. Ongoing check schedule     [who, when, alert thresholds]

Related skills

52-account-structure-global: build campaigns only after tracking is green; utm_content must match ad names.
54-media-plan-global: the objective in the plan determines which events must be tracked.
21-ads-audit-global: periodic tracking audit (match rate, duplicates, EMQ).
12-landing-page-brief-global: the landing page must expose the events and form fields this setup needs.
13-data-analysis-global: reads the clean data this system produces.

Quality checklist

About this skill

Automatic

Marketing & Content pack

SkillSafety

✓ 3 of 3 passed

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minhnv0807 / ai-business-skills

skills/en/53-tracking-setup-global/SKILL.md

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License MITImported 11/1/2026Version v2Bundled 1 file

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What it changes

Track record

Use this skill

Tracking Setup (Global)

Information gathering

Principles

Workflow

1. Choose the measurement architecture

2. Consent management (do this before any tag fires)

3. Install per platform

4. iOS ATT and attribution windows

5. UTM convention

6. GA4 event mapping

7. CRM and offline conversions

8. Verify green before launch

9. Ongoing checks

Discrepancy triage

Troubleshooting

Output structure

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