Automatically document your analytics setup by analyzing tracking code and generating data schemas from tools like Segment, Amplitude, Mixpanel, and more ๐.
๐ Understand Your Tracking โ Effortlessly analyze your codebase for track
calls so you can see all your analytics events, properties, and triggers in one place. No more guessing whatโs being tracked!
๐ Auto-Document Events โ Generates a complete YAML schema that captures all events and properties, including where theyโre implemented in your codebase.
๐ต๏ธโโ๏ธ Track Changes Over Time โ Easily spot unintended changes or ensure your analytics setup remains consistent across updates.
๐ Populate Data Catalogs โ Automatically generate structured documentation that can help feed into your data catalog, making it easier for everyone to understand your events.
Run without installation! Just use:
npx @flisk/analyze-tracking /path/to/project [options]
-g, --generateDescription
: Generate descriptions of fields (default:false
)-o, --output <output_file>
: Name of the output file (default:tracking-schema.yaml
)-c, --customFunction <function_name>
: Specify a custom tracking function
๐ย Important: you must set the OPENAI_API_KEY
environment variable to use generateDescription
Note on Custom Functions ๐ก
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:
yourCustomTrackFunctionName('<event_name>', {
<event_parameters>
});
A clear YAML schema that shows where your events are tracked, their properties, and more. Hereโs 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 theyโre being tracked.
GPT-4o mini is used for generating descriptions of events, properties, and implementations.
See schema.json for a JSON Schema of the output.
Google Analytics
gtag('event', '<event_name>', {
<event_parameters>
});
Segment
analytics.track('<event_name>', {
<event_parameters>
});
Mixpanel
mixpanel.track('<event_name>', {
<event_parameters>
});
Amplitude
amplitude.logEvent('<event_name>', {
<event_parameters>
});
Rudderstack
rudderanalytics.track('<event_name>', {
<event_parameters>
});
mParticle
mParticle.logEvent('<event_name>', {
<event_parameters>
});
PostHog
posthog.capture('<event_name>', {
<event_parameters>
});
Pendo
pendo.track('<event_name>', {
<event_parameters>
});
Heap
heap.track('<event_name>', {
<event_parameters>
});
Snowplow (struct events)
snowplow('trackStructEvent', {
category: '<category>',
action: '<action>',
label: '<label>',
property: '<property>',
value: '<value> '
});
trackStructEvent({
category: '<category>',
action: '<action>',
label: '<label>',
property: '<property>',
value: '<value>'
});
buildStructEvent({
category: '<category>',
action: '<action>',
label: '<label>',
property: '<property>',
value: '<value>'
});
Note: Snowplow Self Describing Events are coming soon!
Weโre actively improving this package. Found a bug? Want to request a feature? Open an issue or contribute directly!