
Exploring Autocapture Events
FreeUnderstand user interactions with PostHog's autocapture.
Free · Opens the source repo
What Exploring Autocapture Events does
The Exploring Autocapture Events skill provides a structured approach to analyzing user interactions captured by PostHog's autocapture feature. This skill is particularly useful for developers and designers who want to gain insights into how users engage with their applications. By leveraging the $autocapture events recorded by posthog-js, users can explore click events, form submissions, and page changes, all while understanding the underlying DOM elements involved in these interactions.
When using this skill, users can start by confirming the presence of autocapture data within their PostHog project. If no data is found, the skill provides guidance on checking project settings or SDK configurations to ensure that autocapture is enabled. Once data is available, users can explore various aspects of user interactions, such as identifying the most clicked elements, analyzing the text of clicked items, and reviewing the relevant URLs. This exploration is facilitated by utilizing materialized columns that provide quick access to essential element fields without the need for complex parsing.
After gaining an understanding of user interactions, the skill guides users in identifying and refining CSS selectors for specific interactions. This includes evaluating selector uniqueness to ensure that the chosen selectors accurately capture the intended events without interference from unrelated interactions. By layering additional filters, such as text or URL constraints, users can further refine their queries to achieve precise insights.
This skill is designed for teams utilizing posthog-js autocapture, making it an essential tool for those looking to enhance their understanding of user behavior and optimize their applications based on real interaction data.
When to use it
Use this skill when you need to explore user interactions, find CSS selectors for elements, or build actions based on click events in applications using posthog-js.
When not to use it
This skill is not suitable for projects that do not utilize posthog-js autocapture, as its functionality is specifically tailored to that environment.
What you can build with it
Analyzing Click Events
Use the skill to explore which elements users are clicking most frequently, helping to identify popular features or areas for improvement.
Building Actions from Clicks
After identifying key interactions, leverage the skill to create actions based on specific click events, enhancing user engagement.
Refining CSS Selectors
Utilize the skill to find and evaluate CSS selectors for elements, ensuring they accurately target the intended interactions without overlap.
How to install Exploring Autocapture Events
View source1. Install with the skills CLI
npx skills add posthog/posthog/exploring-autocapture-events --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by posthogExploring autocapture events
if users opt in then posthog-js automatically captures clicks, form submissions, and page changes as $autocapture events.
Each event records the clicked DOM element and its ancestors in the elements_chain column.
$autocapture is intentionally excluded from the posthog:read-data-schema taxonomy
because it is only useful with autocapture-specific filters (selector, tag, text, href).
This skill fills that gap.
Materialized columns
The events table provides fast access to common element fields without parsing the full chain string.
| Column | Type | Description |
|---|---|---|
elements_chain | String | Full semicolon-separated element chain (see format reference) |
elements_chain_href | String | Last href value from the chain |
elements_chain_texts | Array(String) | All text values from elements |
elements_chain_ids | Array(String) | All id attribute values |
elements_chain_elements | Array(String) | Useful tag names: a, button, input, select, textarea, label |
Use materialized columns for exploration queries whenever possible — they avoid regex parsing.
Canonical autocapture properties
Every $autocapture event from posthog-js ships with a fixed set of properties.
Do not query the schema to "look them up" — they are these:
| Property | Examples | Notes |
|---|---|---|
$event_type | click, submit, change | the kind of interaction |
$el_text | Sign up, Submit | text of the clicked element |
$current_url | https://app.example.com/pricing | page the interaction happened on |
$elements_chain | semicolon-separated chain | parsed via the elements_chain* materialized columns above |
Standard event properties ($browser, $os, $device_type, etc.) are also present.
Workflow
1. Confirm autocapture data exists
Run a count query before doing anything else. If the count is zero, autocapture may be disabled. There are two ways this happens:
- Project settings — the team can set
autocapture_opt_outin PostHog project settings - SDK config — the posthog-js
init()call can passautocapture: false
Tell the user if no data is found so they can check both settings.
SELECT count() as cnt
FROM events
WHERE event = '$autocapture'
AND timestamp > now() - INTERVAL 7 DAY
2. Explore what users are interacting with
Start broad using the materialized columns. The goal is to understand what users are clicking before narrowing down.
Useful explorations:
- Top clicked tag names (via
elements_chain_elements) - Top clicked text values (via
elements_chain_texts) - Top clicked hrefs (via
elements_chain_href) - Raw
elements_chainvalues for a specific page (filtered byproperties.$current_url)
See example queries for all patterns.
3. Find candidate selectors
Once the user identifies an interaction they care about, find a CSS selector that identifies it.
Priority order for selector attributes (best first):
data-attror otherdata-*attributes — highest specificity, stable across deploys, developer-intended anchors. Search withmatch(elements_chain, 'data-attr=')orextractAll.- Element ID (
attr_id) — also highly stable, queryable viaelements_chain_ids. - Tag + class combination — moderately stable but classes change with CSS refactors.
- Text content — fragile (changes with copy edits, i18n) but sometimes the only option.
- Tag name alone — too broad on its own, useful as a qualifier.
When a data-attr value is found, construct a selector like [data-attr="value"] or button[data-attr="value"].
4. Evaluate selector uniqueness
A selector is only useful if it matches the intended interaction and not unrelated events.
Run a uniqueness check using elements_chain =~ with the regex pattern for the selector.
Then sample matching events to inspect what the selector actually captures.
Compare the count against total autocapture volume to understand selectivity.
A good selector matches a single logical interaction. If it matches too many distinct elements, refine it in the next step.
5. Refine with additional filters
If the selector alone is not unique enough, layer on additional filters:
- Text filter — match by element text content using
elements_chain_texts - URL filter — restrict to a specific page using
properties.$current_url - Href filter — match by link target using
elements_chain_href
Re-run the uniqueness check after each refinement. Only include filters that are needed — fewer filters means more resilience to minor DOM changes.
6. Filter autocapture inside an insight query
When the user wants a funnel, trend, or other insight, the filter shape is different from HogQL.
Each step in a FunnelsQuery / TrendsQuery is an EventsNode (or ActionsNode) with event: "$autocapture" and a properties array.
Two distinct property type values matter — they are not interchangeable:
type: "element"— keys:selector,tag_name,text,href. Matched against the parsedelements_chain. Operator support is split:selectorandtag_nameonly supportexactandis_not— any other operator is rejected by the query engine and the query errors.textandhrefaccept the full string operator set (exact,is_not,icontains,not_icontains,regex,not_regex,is_set,is_not_set).
type: "event"— keys: any of the canonical autocapture properties ($event_type,$el_text,$current_url) or anything else on the event. Standard event-property operators (exact,icontains,regex, etc.).
Example funnel from clicking one button to clicking another:
{
"kind": "FunnelsQuery",
"series": [
{
"kind": "EventsNode",
"event": "$autocapture",
"properties": [
{
"type": "element",
"key": "selector",
"value": ["[data-attr=\"autocapture-series-save-as-action-banner-shown\"]"],
"operator": "exact"
}
]
},
{
"kind": "EventsNode",
"event": "$autocapture",
"properties": [
{
"type": "element",
"key": "selector",
"value": ["[data-attr=\"autocapture-save-as-action\"]"],
"operator": "exact"
}
]
}
]
}
Two things easy to get wrong:
valueis an array even when matching a single selector- The selector string includes the
[data-attr="..."]wrapper — it is a CSS selector, not a bare attribute value
Decision rule: prefer an action (ActionsNode referencing an existing action — see Step 8) when the interaction will be referenced more than once; inline type: "element" / type: "event" filters when it's a one-off insight; raw HogQL (Step 7) when joining across events or doing custom aggregations.
7. Use in ad-hoc queries
The discovered selector can be used directly in HogQL without creating an action.
Trends — count matching clicks over time:
SELECT
toStartOfDay(timestamp) as day,
count() as clicks
FROM events
WHERE event = '$autocapture'
AND timestamp > now() - INTERVAL 14 DAY
AND elements_chain =~ '(^|;)button.*?data-attr="checkout"'
GROUP BY day
ORDER BY day
Funnel — pageview to click conversion:
SELECT
person_id,
first_pageview,
first_click_after
FROM (
SELECT
p.person_id,
p.pageview_time as first_pageview,
min(c.click_time) as first_click_after
FROM (
SELECT person_id, min(timestamp) as pageview_time
FROM events
WHERE event = '$pageview'
AND timestamp > now() - INTERVAL 14 DAY
AND properties.$current_url ILIKE '%/pricing%'
GROUP BY person_id
) p
INNER JOIN (
SELECT person_id, timestamp as click_time
FROM events
WHERE event = '$autocapture'
AND timestamp > now() - INTERVAL 14 DAY
AND elements_chain =~ '(^|;)button.*?data-attr="signup"'
) c ON p.person_id = c.person_id AND c.click_time > p.pageview_time
GROUP BY p.person_id, p.pageview_time
)
For recurring analysis, prefer creating an action (next step) or using posthog:query-trends / posthog:query-funnel with the action.
8. Create an action
Actions are the durable version of ad-hoc selector queries.
Once the criteria uniquely identify the interaction, create an action using posthog:action-create.
Construct the step with only the filters needed for uniqueness:
{
"name": "Clicked checkout button",
"steps": [
{
"event": "$autocapture",
"selector": "button[data-attr='checkout']",
"text": "Complete Purchase",
"text_matching": "exact",
"url": "/checkout",
"url_matching": "contains"
}
]
}
Available step fields for $autocapture:
selector— CSS selector (e.g.button[data-attr='checkout'])tag_name— HTML tag name (e.g.button,a,input)text/text_matching— element text (exact,contains, orregex)href/href_matching— link href (exact,contains, orregex)url/url_matching— page URL (exact,contains, orregex)
After creation, verify with matchesAction():
SELECT count() as matching_events
FROM events
WHERE matchesAction('Clicked checkout button')
AND timestamp > now() - INTERVAL 7 DAY
Tips
- Always set timestamp filters —
$autocaptureis high volume - Use
LIMITgenerously when samplingelements_chain— the strings can be long - The
elements_chain =~operator matches CSS selectors as regex internally; prefer materialized columns when possible for performance - This workflow only applies to posthog-js — other SDKs do not capture elements
Frequently asked questions about Exploring Autocapture Events
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