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Finds the most informative session recording linked to an error tracking issue. Use when a user has an error tracking issue ID and wants to watch a replay showing what the user was doing when the error occurred. Ranks linked sessions by recency, activity score, and journey

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posthog
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Install
$ npx -y skills add PostHog/ai-plugin --skill finding-replay-for-issue --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/finding-replay-for-issue

Context preview

The summary Claude sees to decide when to auto-load this skill.

Finds the most informative session recording linked to an error tracking issue. Use when a user has an error tracking issue ID and wants to watch a replay showing what the user was doing when the error occurred. Ranks linked sessions by recency, activity score, and journey

SKILL.md

finding-replay-for-issue.SKILL.md
name: finding-replay-for-issue
description: >
  Finds the most informative session recording linked to an error tracking issue.
  Use when a user has an error tracking issue ID and wants to watch a replay showing
  what the user was doing when the error occurred. Ranks linked sessions by recency,
  activity score, and journey completeness, then summarizes the pre-error context.
  Replaces blind session picking from potentially hundreds of linked recordings.

Finding the best replay for an error tracking issue

When a user says "show me a replay for this error" or "find a recording for issue X", the goal isn't just any linked session — it's the one that best shows what led to the error. Popular issues can have hundreds of linked sessions, and most are crash-only fragments or duplicate occurrences. This skill picks the most useful one.

Available tools

| Tool | Purpose | | --------------------------------------- | ---------------------------------------------------------- | | `posthog:query-error-tracking-issue` | Get issue details (fingerprint, status, volume) | | `posthog:execute-sql` | Query exception events to find linked sessions | | `posthog:query-session-recordings-list` | Fetch recording metadata for candidate sessions | | `posthog:session-recording-get` | Get full details for the selected recording | | `posthog:vision-observations-list` | Check for an existing Replay Vision AI summary | | `posthog:vision-scanners-list` | Find summarizer scanners (`scanner_type=summarizer`) | | `posthog:vision-scanners-scan-session` | Run a summarizer scanner on the recording (optional, slow) |

Workflow

Step 1 — Get the issue details

Fetch the error tracking issue to understand what you're looking for:

posthog:query-error-tracking-issue
{
  "issueId": "<issue_id>"
}

Note the issue's `fingerprint`, `name`, and `description` — you'll need the fingerprint to find linked sessions.

Step 2 — Find sessions with this error

Query exception events to get session IDs where this error occurred. Order by recency and include basic context:

posthog:execute-sql
SELECT
    $session_id AS session_id,
    count() AS occurrences,
    min(timestamp) AS first_seen,
    max(timestamp) AS last_seen,
    any(properties.$current_url) AS url
FROM events
WHERE event = '$exception'
    AND properties.$exception_fingerprint = '<fingerprint>'
    AND $session_id IS NOT NULL
    AND timestamp > now() - INTERVAL 30 DAY
GROUP BY session_id
ORDER BY last_seen DESC
LIMIT 20

This gives you up to 20 candidate sessions. More candidates means better selection.

Step 3 — Rank the candidates

Fetch recording metadata for the candidate sessions to rank them:

posthog:query-session-recordings-list
{
  "session_ids": ["<id1>", "<id2>", "<id3>", ...],
  "date_from": "-30d"
}

Pick the best recording by filtering out bad candidates, then ranking what's left:

**Filter out:**

  • Sessions under 10 seconds (crash-only fragments, no pre-error context)
  • Sessions over 1 hour (too much data to load, error is a needle in a haystack)

**Rank by:**

1. **Sweet-spot duration** — 2-15 minutes is ideal. Long enough to show the user's journey before the error, short enough to be practical to watch or summarize. 2. **Active time ratio** — compare `active_seconds` to `recording_duration`. A 20-minute recording with 10 seconds of activity is mostly idle tabs — the user walked away. Prefer sessions where `active_seconds / recording_duration` is above 0.3 (30%). 3. **Activity score** — higher `activity_score` means the user was actively interacting, not idle. More interesting to watch. 4. **Recency** — more recent sessions reflect current app behavior.

Step 4 — Present the finding

Fetch full details for the selected recording:

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

Present to the user:

  • **The recording** with a link to watch it
  • **Why this one** — briefly explain the selection ("longest session with the error,

user was browsing 3 pages before hitting it")

  • **Pre-error context** — what pages the user visited and key actions before the exception,

derived from the events query in step 2 (the `url` and `first_seen` columns)

  • **Error frequency** — how many times the error occurred in this session

Optional: AI summary via Replay Vision

If the user wants a narrative summary without watching, use Replay Vision — "check-then-scan", since a scanner can only observe a given session once.

1. **Check for an existing summary** on the selected recording:

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

If an observation has `scanner_snapshot.scanner_type` `summarizer` and `status` `succeeded`, read `scanner_result.model_output` (`title`, `summary`, `intent`, `outcome`, `friction_points`, `keywords`) — done.

2. **Find a summarizer scanner** if none exists:

   posthog:vision-scanners-list
   {
     "scanner_type": "summarizer"
   }

One → use it. More than one → ask the user which (show name + prompt). None → offer to create one via the `creating-replay-vision-scanners` skill.

3. **Scan the recording** with the chosen scanner (async, several minutes):

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

4. **Retrieve** by polling `vision-observations-list` until `succeeded`.

Tips

  • If all candidate sessions are very short (<10 seconds), the error likely crashes

the page immediately. Note this — it's useful context even without a long replay.

  • When the issue has very few linked sessions (<3), skip the ranking and just present

what's available with a note abo

Read more
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