investigating-replay

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

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

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

Step 3 — Check for linked error tracking issues

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

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

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 via Replay Vision

If the user wants a deeper analysis without reading through events manually, offer a Replay Vision summary. Follow "check-then-scan" — don't scan blindly, a scanner can only observe a given session once.

1. Check for an existing summary. A scheduled scanner may already have one:

   posthog:vision-observations-list
   {
     "session_id": "<session_id>"
   }

   Look for an observation where scanner_snapshot.scanner_type is summarizer and status is succeeded. If found, read scanner_result.model_output (title, summary, intent, outcome, friction_points, keywords) — done, no new scan needed.

2. Find a summarizer scanner if none exists yet:

   posthog:vision-scanners-list
   {
     "scanner_type": "summarizer"
   }
   • Exactly one → use it.
   • More than one → show the user the scanners (name + prompt) and ask which to use.
   • None → no summarizer scanner exists. See No summarizer scanner? Run a temporary one below.

3. Scan the session with the chosen scanner. Warn this is async and takes several minutes (rasterize + LLM):

   posthog:vision-scanners-scan-session
   {
     "id": "<scanner_id>",
     "session_id": "<session_id>"
   }

4. Retrieve the result by polling vision-observations-list (step 1) until the new observation reaches succeeded.

No summarizer scanner? Run a temporary one

If the project has no summarizer scanner, you can still produce a one-off summary with a throwaway scanner — but ask the user's permission before creating anything.

1. Ask permission to create a temporary summarizer scanner just to summarize this one session.

2. Create it disabled so it never sweeps on a schedule — a disabled scanner only runs when you trigger it on demand, so it won't touch other sessions or burn quota in the background:

   posthog:vision-scanners-create
   {
     "name": "Temporary on-demand summary",
     "scanner_type": "summarizer",
     "scanner_config": {
       "prompt": "Summarize what the user was trying to do, whether they succeeded, and any friction they hit."
     },
     "query": { "kind": "RecordingsQuery" },
     "model": "gemini-3-flash-preview",
     "enabled": false
   }

3. Scan this session on demand with the new scanner, then poll for the result:

   posthog:vision-scanners-scan-session
   {
     "id": "<new_scanner_id>",
     "session_id": "<session_id>"
   }

   Poll vision-observations-list until the observation reaches succeeded and read scanner_result.model_output.

4. Ask whether to keep or delete the scanner. Once you have the observation, ask the user if they want to keep the temporary scanner or delete it with vision-scanners-delete. Deleting is safe: the summary you just read is also emitted as an event that persists after the scanner is gone, so cleaning up the temporary scanner does not lose the result.

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.