investigating-replay

name

investigating-replay

description

Investigates a session recording by gathering metadata, person profile, same-session events, and linked error tracking issues in one pass. Use when a user provides a recording or session ID and wants to understand what happened — who the user was, what they did, what errors occurred, and whether there are related error tracking issues. Replaces the manual chain of session-recording-get, persons-retrieve, execute-sql, and query-error-tracking-issues-list.

Investigating a session recording

When a user asks "what happened in this session?" or provides a recording/session ID to investigate, gather all relevant context in parallel rather than making them ask for each piece.

Available tools

Tool	Purpose
posthog:session-recording-get	Recording metadata (duration, counts, status)
posthog:persons-retrieve	Person profile (properties, distinct IDs)
posthog:execute-sql	Query events, errors, and page views in session
posthog:query-error-tracking-issues-list	Find error tracking issues linked to the session
posthog:session-recording-summarize	AI-generated summary (slow, ~5 min, optional)

Workflow

Step 1 — Get recording metadata and person profile

Start with the recording to get metadata and the person's distinct ID:

posthog:session-recording-get
{
  "id": "<recording_id>"
}

The response includes distinct_id, person, duration, interaction counts, console error counts, and viewing status. Use the distinct_id to fetch the full person profile:

posthog:persons-retrieve
{
  "id": "<person_uuid_from_recording>"
}

Step 2 — Query same-session events

Get the timeline of what the user did during the session:

posthog:execute-sql
SELECT
    timestamp,
    event,
    properties.$current_url AS url,
    properties.$browser AS browser,
    properties.$os AS os,
    properties.$device_type AS device_type,
    properties.$screen_width AS screen_width
FROM events
WHERE $session_id = '<session_id>'
ORDER BY timestamp ASC
LIMIT 200

For sessions with many events, focus on the most informative ones:

posthog:execute-sql
SELECT
    timestamp,
    event,
    properties.$current_url AS url,
    if(event = '$exception', properties.$exception_message, null) AS exception_message,
    if(event = '$exception', properties.$exception_type, null) AS exception_type
FROM events
WHERE $session_id = '<session_id>'
    AND event IN ('$pageview', '$pageleave', '$autocapture', '$exception', '$rageclick')
ORDER BY timestamp ASC
LIMIT 100

Step 3 — Check for linked error tracking issues

If the recording has console errors or exceptions, find related error tracking issues:

posthog:execute-sql
SELECT DISTINCT
    properties.$exception_fingerprint AS fingerprint,
    properties.$exception_type AS type,
    properties.$exception_message AS message,
    count() AS occurrences
FROM events
WHERE $session_id = '<session_id>'
    AND event = '$exception'
GROUP BY fingerprint, type, message
ORDER BY occurrences DESC
LIMIT 10

If fingerprints are found, search for the corresponding error tracking issues to provide links and status:

posthog:query-error-tracking-issues-list
{
  "searchQuery": "<exception_type or message>"
}

Step 4 — Synthesize the investigation

Present the findings as a coherent narrative:

1. Who — person properties (name, email, country, plan, etc.)
2. What — sequence of pages visited and key actions taken
3. Problems — exceptions, console errors, rage clicks, and their frequency
4. Related issues — linked error tracking issues with their status (active/resolved)
5. Context — session duration, device/browser, activity score

Optional: AI summary

If the user wants a deeper analysis without reading through events manually, offer session-recording-summarize. Warn that first-time summaries take ~5 minutes:

posthog:session-recording-summarize
{
  "session_ids": ["<session_id>"]
}

Tips

• Run steps 1-3 in parallel when possible — they're independent queries.
• If the recording has very few events, the session was likely very short. Note this rather than suggesting something is broken.
• Console error count from the recording metadata is a good signal for whether to dig into exceptions. If it's 0, skip step 3.
• The start_url from the recording tells you where the user's journey began — use this to frame the narrative.
• If person is null on the recording, the user was anonymous. Person properties won't be available, but events still are.