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Exploring Autocapture Events

PostHogOfficialPublished by PostHog

  • Skill
  • Workflow
  • Data and AI
  • MIT
  • No issues found

From the author

Guides exploration of $autocapture events captured by posthog-js to understand user interactions, find CSS selectors (especially data-attr attributes), evaluate selector uniqueness, query matching clicks ad-hoc, and create actions. Use when the user asks about autocapture data, wants to find what users are clicking, needs to build actions from click events, asks about elements_chain, wants to build a trend or funnel filtered by clicks or other autocapture interactions, asks which properties autocapture sends, or asks how to filter $autocapture events. Only applies to projects using posthog-js autocapture.
— the description by PostHog

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured workflow for analyzing $autocapture events generated by posthog-js. It covers the process of confirming data availability, exploring user interaction patterns using materialized columns, identifying stable CSS selectors, evaluating selector uniqueness, and refining filters to create durable actions or ad-hoc insights. It is designed to help users move from raw event data to meaningful product analytics without needing to manually instrument every click.

What it does

  • Verifies the presence of $autocapture data in your project.
  • Explores top-clicked elements, text, and URLs using materialized columns.
  • Identifies stable CSS selectors using data-attributes and element IDs.
  • Evaluates selector uniqueness to ensure accurate event tracking.
  • Refines event filters using text, URL, and href criteria.
  • Creates durable actions or ad-hoc HogQL queries for trends and funnels.

When to use it

  • When you need to understand what users are clicking on your site.
  • When you want to build a funnel or trend based on specific user interactions.
  • When you need to create an action for a button or link that isn't manually tracked.
  • When you need to debug or filter high-volume $autocapture event data.

Advantages

  • Reduces reliance on manual event instrumentation.
  • Leverages materialized columns for faster, more efficient queries.
  • Provides a clear hierarchy for selecting stable, resilient CSS selectors.
  • Enables precise filtering to avoid capturing unintended interactions.

Usage examples

“How can I see what users are clicking on my pricing page?”
The agent will guide you to use a query filtering by properties.$current_url and aggregating the elements_chain_texts or elements_chain_elements to identify top interactions.
“I need to create a funnel for users who click the 'Sign Up' button.”
The agent will help you find a unique CSS selector for that button and provide the JSON structure for a FunnelsQuery using that selector.
“How do I check if my autocapture data is working?”
The agent will provide a count query to run against the events table to verify if $autocapture events are being recorded.
“My selector is matching too many things, how do I fix it?”
The agent will suggest adding additional filters like element text, current URL, or specific href values to narrow down the scope of the selector.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/posthog/exploring-autocapture-events/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip exploring-autocapture-events.zip -d .agents/skills

Documentation by PostHog

Exploring 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.

ColumnTypeDescription
elements_chainStringFull semicolon-separated element chain (see format reference)
elements_chain_hrefStringLast href value from the chain
elements_chain_textsArray(String)All text values from elements
elements_chain_idsArray(String)All id attribute values
elements_chain_elementsArray(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:

PropertyExamplesNotes
$event_typeclick, submit, changethe kind of interaction
$el_textSign up, Submittext of the clicked element
$current_urlhttps://app.example.com/pricingpage the interaction happened on
$elements_chainsemicolon-separated chainparsed 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_out in PostHog project settings

  • SDK config — the posthog-js init() call can pass autocapture: 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_chain values for a specific page (filtered by properties.$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):

  1. data-attr or other data-* attributes — highest specificity, stable across deploys, developer-intended anchors. Search with match(elements_chain, 'data-attr=') or extractAll.

  2. Element ID (attr_id) — also highly stable, queryable via elements_chain_ids.

  3. Tag + class combination — moderately stable but classes change with CSS refactors.

  4. Text content — fragile (changes with copy edits, i18n) but sometimes the only option.

  5. 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 parsed elements_chain. Operator support is split:

    • selector and tag_name only support exact and is_not — any other operator is rejected by the query engine and the query errors.

    • text and href accept 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:

  • value is 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, or regex)

  • href / href_matching — link href (exact, contains, or regex)

  • url / url_matching — page URL (exact, contains, or regex)

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 — $autocapture is high volume

  • Use LIMIT generously when sampling elements_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

Files

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

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Attribution and licence

Published by
PostHog
Publisher
PostHog (Official)
Source
PostHog/skills · skills/omnibus/exploring-autocapture-events · commit a5d30e7
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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