@flisk/analyze-tracking v0.7.4

@flisk/analyze-tracking

Automatically document your analytics setup by analyzing tracking code and generating data schemas from tools like Segment, Amplitude, Mixpanel, and more 🚀

Why Use @flisk/analyze-tracking?

📊 Understand Your Tracking – Effortlessly analyze your codebase for track calls so you can see all your analytics events, properties, and triggers in one place. No more guessing what's being tracked!

🔍 Auto-Document Events – Generates a complete YAML schema that captures all events and properties, including where they're implemented in your codebase.

🕵️‍♂️ Track Changes Over Time – Easily spot unintended changes or ensure your analytics setup remains consistent across updates.

📚 Populate Data Catalogs – Automatically generate structured documentation that can help feed into your data catalog, making it easier for everyone to understand your events.

Quick Start

Run without installation! Just use:

npx @flisk/analyze-tracking /path/to/project [options]

Key Options:

• -g, --generateDescription: Generate descriptions of fields (default: false)
• -p, --provider <provider>: Specify a provider (options: openai, gemini)
• -m, --model <model>: Specify a model (ex: gpt-4.1-nano, gpt-4o-mini, gemini-2.0-flash-lite-001)
• -o, --output <output_file>: Name of the output file (default: tracking-schema.yaml)
• -c, --customFunction <function_name>: Specify a custom tracking function
• --format <format>: Output format, either yaml (default) or json. If an invalid value is provided, the CLI will exit with an error.
• --stdout: Print the output to the terminal instead of writing to a file (works with both YAML and JSON)

🔑  Important: If you are using generateDescription, you must set the appropriate credentials for the LLM provider you are using as an environment variable. OpenAI uses OPENAI_API_KEY and Google Vertex AI uses GOOGLE_APPLICATION_CREDENTIALS.

Use this if you have your own in-house tracker or a wrapper function that calls other tracking libraries.

We currently only support functions that follow the following format:

JavaScript/TypeScript/Python/Ruby:

yourCustomTrackFunctionName('<event_name>', {
  <event_parameters>
});

Go:

yourCustomTrackFunctionName("<event_name>", map[string]any{}{
  "<property_name>": "<property_value>",
})

What's Generated?

A clear YAML schema that shows where your events are tracked, their properties, and more. Here's an example:

version: 1
source:
  repository: <repository_url>
  commit: <commit_sha>
  timestamp: <commit_timestamp>
events:
  <event_name>:
    description: <ai_generated_description>
    implementations:
      - description: <ai_generated_description>
        path: <path_to_file>
        line: <line_number>
        function: <function_name>
        destination: <platform_name>
    properties:
      <property_name>:
        description: <ai_generated_description>
        type: <property_type>

Use this to understand where your events live in the code and how they're being tracked.

Your LLM of choice is used for generating descriptions of events, properties, and implementations.

See schema.json for a JSON Schema of the output.

Supported tracking libraries & languages

✳️ Rudderstack's SDKs often use the same format as Segment, so Rudderstack events may be detected as Segment events.

SDKs for supported libraries

JavaScript/TypeScript

gtag('event', '<event_name>', {
  '<property_name>': '<property_value>'
});

JavaScript/TypeScript

analytics.track('<event_name>', {
  '<property_name>': '<property_value>'
});

Python

analytics.track('<event_name>', {
  '<property_name>': '<property_value>'
})

Ruby

Analytics.track(
  event: '<event_name>',
  properties: {
    '<property_name>': '<property_value>'
  }
)

Go

client.Enqueue(analytics.Track{
  UserId: "user-id",
  Event:  "<event_name>",
  Properties: analytics.NewProperties().
    Set("<property_name>", "<property_value>"),
})

JavaScript/TypeScript

mixpanel.track('<event_name>', {
  '<property_name>': '<property_value>'
});

Python

mixpanel.track('<event_name>', {
  '<property_name>': '<property_value>'
})

Ruby

tracker.track('<distinct_id>', '<event_name>', {
  '<property_name>': '<property_value>'
})

Go

ctx := context.Background()
mp := mixpanel.NewApiClient("YOUR_PROJECT_TOKEN")
mp.Track(ctx, []*mixpanel.Event{
  mp.NewEvent("<event_name>", "", map[string]any{}{
    "<property_name>": "<property_value>",
  }),
})

JavaScript/TypeScript

amplitude.track('<event_name>', {
  <event_parameters>
});

Python

client.track(
  BaseEvent(
    event_type="<event_name>",
    user_id="<user_id>",
    event_properties={
      "<property_name>": "<property_value>",
    },
  )
)

Go

client.Track(amplitude.Event{
  UserID:    "<user_id>",
  EventType: "<event_name>",
  EventProperties: map[string]any{}{
    "<property_name>": "<property_value>",
  },
})

JavaScript/TypeScript

rudderanalytics.track('<event_name>', {
  <event_parameters>
});

Python

rudder_analytics.track('<event_name>', {
  '<property_name>': '<property_value>'
})

Ruby

analytics.track(
  user_id: '<user_id>',
  event: '<event_name>',
  properties: {
    '<property_name>': '<property_value>'
  }
)

Go

client.Enqueue(analytics.Track{
  UserId: "<user_id>",
  Event:  "<event_name>",
  Properties: analytics.NewProperties().
    Set("<property_name>", "<property_value>"),
})

JavaScript/TypeScript

mParticle.logEvent('<event_name>', mParticle.EventType.<event_type>, {
  '<property_name>': '<property_value>'
});

JavaScript/TypeScript

posthog.capture('<event_name>', {
  '<property_name>': '<property_value>'
});

Python

posthog.capture('distinct_id', '<event_name>', {
  '<property_name>': '<property_value>'
})
# Or
posthog.capture(
  'distinct_id',
  event='<event_name>',
  properties={
    '<property_name>': '<property_value>'
  }
)

Ruby

posthog.capture({
  distinct_id: '<distinct_id>',
  event: '<event_name>',
  properties: {
    '<property_name>': '<property_value>'
  }
})

Go

client.Enqueue(posthog.Capture{
  DistinctId: "<distinct_id>",
  Event:      "<event_name>",
  Properties: posthog.NewProperties().
    Set("<property_name>", "<property_value>"),
})

JavaScript/TypeScript

pendo.track('<event_name>', {
  <event_parameters>
});

Python

pendo.track('<event_name>', {
  '<property_name>': '<property_value>'
})

JavaScript/TypeScript

heap.track('<event_name>', {
  <event_parameters>
});

Python

heap.track('<event_name>', {
  '<property_name>': '<property_value>'
})

JavaScript/TypeScript

tracker.track(buildStructEvent({
  action: '<event_name>',
  category: '<category>',
  label: '<label>',
  property: '<property>',
  value: <value>
}));

Python

tracker.track(StructuredEvent(
  action="<event_name>",
  category="<category>",
  label="<label>",
  property_="<property>",
  value=<value>,
))

Ruby

tracker.track_struct_event(
  action: '<event_name>',
  category: '<category>',
  label: '<label>',
  property: '<property>',
  value: <value>
)

Go

tracker.TrackStructEvent(sp.StructuredEvent{
		Action:   sp.NewString("<event_name>"),
		Category: sp.NewString("<category>"),
		Label:    sp.NewString("<label>"),
		Property: sp.NewString("<property>"),
		Value:    sp.NewFloat64(<value>),
	})

Contribute

We're actively improving this package. Found a bug? Have a feature request? Open an issue or submit a pull request!