/finding-replay-for-issue
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
Claude Code
$ npx -y skills add PostHog/ai-plugin --skill finding-replay-for-issue --agent claude-code
Codex
$ npx skills add PostHog/ai-plugin --skill finding-replay-for-issue -a codex -y
Cursor
$ npx skills add PostHog/ai-plugin --skill finding-replay-for-issue -a cursor -y
Gemini CLI
$ npx skills add PostHog/ai-plugin --skill finding-replay-for-issue -a gemini-cli -y
GitHub Copilot
$ npx skills add PostHog/ai-plugin --skill finding-replay-for-issue -a github-copilot -y
OpenCode
$ npx skills add PostHog/ai-plugin --skill finding-replay-for-issue -a opencode -y
Windsurf
$ npx skills add PostHog/ai-plugin --skill finding-replay-for-issue -a windsurf -y
SKILL.md
finding-replay-for-issue.SKILL.mdname: 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 20This 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
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 20This 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
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Questions about finding-replay-for-issue.
- Which coding agents can use finding-replay-for-issue?
- finding-replay-for-issue installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

