Which user action triggers which error?

Why this matters

A stack trace tells you the line that threw. It does not tell you what the user did to get there. “TypeError on line 88” — but did they click checkout? Search? Toggle a filter? Three different paths, three different fixes.

In a Sentry+Mixpanel world you have errors in one tool and behavior in another. The data lives in different databases with different user identifiers. You eyeball timestamps in two tabs and guess.

Agentry puts both in the same store with the same distinct_id key. One HogQL query does the asof-join: for each error event, find the most recent analytics event by the same user within the previous 60 seconds. The “what did the user just do” answer falls out in one query.

What you get

• For each top-N error fingerprint: the most common analytics event in the 60 seconds before
• A confidence score (how concentrated is the preceding-action distribution?)
• A “reproduction recipe” for the top error: “click X, click Y, then the bug fires”

Walk through it

agentry_list_cases {
  project_id: "default",
  status: "open",
  since: "7d",
  limit: 5,
  order_by: "event_count"
}

{
  "cases": [
    { "id": "c_f72a", "fingerprint": "f_72a", "message": "TypeError on user.plan", "event_count": 412 },
    { "id": "c_2d8e", "fingerprint": "f_2d8e", "message": "checkout 500: stripe timeout", "event_count": 89 },
    { "id": "c_91dd", "fingerprint": "f_91dd", "message": "Failed to load /api/projects", "event_count": 64 }
  ]
}

agentry_analytics_query {
  project_id: "default",
  hogql: "WITH errors AS (SELECT distinct_id, timestamp AS err_ts, properties.fingerprint AS fp FROM events WHERE event = '$exception' AND properties.fingerprint IN ('f_72a','f_2d8e','f_91dd') AND timestamp >= now() - INTERVAL 7 DAY), preceding AS (SELECT e.fp AS fp, a.event AS preceding_event, e.distinct_id AS did, a.timestamp AS act_ts, e.err_ts FROM errors e ASOF LEFT JOIN events a ON e.distinct_id = a.distinct_id AND a.timestamp <= e.err_ts WHERE a.event != '$exception' AND a.timestamp >= e.err_ts - INTERVAL 60 SECOND) SELECT fp, preceding_event, count() AS cnt FROM preceding GROUP BY fp, preceding_event ORDER BY fp, cnt DESC"
}

{
  "rows": [
    { "fp": "f_72a", "preceding_event": "clicked_account_settings", "cnt": 388 },
    { "fp": "f_72a", "preceding_event": "page_loaded:/settings", "cnt": 16 },
    { "fp": "f_72a", "preceding_event": "$pageview", "cnt": 8 },
    { "fp": "f_2d8e", "preceding_event": "clicked_checkout_button", "cnt": 84 },
    { "fp": "f_2d8e", "preceding_event": "submitted_payment_form", "cnt": 5 },
    { "fp": "f_91dd", "preceding_event": "clicked_projects_tab", "cnt": 42 },
    { "fp": "f_91dd", "preceding_event": "$pageview", "cnt": 18 },
    { "fp": "f_91dd", "preceding_event": "applied_filter", "cnt": 4 }
  ]
}

The output

Reproduction recipes (top 3 errors, 7d)

f_72a    TypeError on user.plan
         Trigger:  clicked_account_settings (94%)
         Repro:    [log in as free tier] → [click Account Settings]
         Confidence: HIGH

f_2d8e   checkout 500: stripe timeout
         Trigger:  clicked_checkout_button (94%)
         Repro:    [add item to cart] → [click Checkout]
         Confidence: HIGH

f_91dd   Failed to load /api/projects
         Trigger:  clicked_projects_tab (65%)
                   $pageview /projects direct (29%)
                   applied_filter (6%)  ← worth investigating
         Repro:    [click Projects tab] — usually
                   [apply a filter] — sometimes, maybe a slower variant
         Confidence: MEDIUM (multi-modal)

Next: f_91dd's filter sub-pattern is suspicious. Want me to find which
      specific filter values are over-represented in the 6%?

Setting it up

The recipe requires three things:

1. Errors and analytics in the same project — true by default with Agentry, both go to the same DSN.
2. The same distinct_id on both — set user.id on error events to match what you use for analytics.
3. Useful analytics events — $pageview is fine but clicked_X semantic events make the repro recipe specific.

// Set distinct_id on every error
await fetch(`https://api.agentry.sh/v1/logs/${PROJECT_ID}/`, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.AGENTRY_DSN}`,
    "Content-Type": "application/json",
    "User-Agent": "myapp/1.0",  // REQUIRED — Cloudflare 403s default UAs
  },
  body: JSON.stringify({
    message: err.message,
    stack: err.stack,
    user: { id: currentUser?.email ?? visitorId },  // ← same as analytics
  }),
});

// Send semantic events on key interactions (not just $pageview)
function trackClick(eventName: string, properties?: Record<string, unknown>) {
  return fetch(`https://api.agentry.sh/v1/analytics/${PROJECT_ID}/`, {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.AGENTRY_DSN}`,
      "Content-Type": "application/json",
      "User-Agent": "myapp/1.0",
    },
    body: JSON.stringify({
      event: eventName,
      distinct_id: currentUser?.email ?? visitorId,
      properties,
    }),
  });
}

// In your UI:
<button onClick={() => { trackClick("clicked_checkout_button"); goToCheckout(); }}>
  Checkout
</button>

$pageview alone gives you “they were on /settings” but clicked_account_settings gives you “they clicked the menu item.” For the asof-join to produce useful repro recipes, lean toward semantic events.

Variations

• “For error c_f72a, give me the FULL pre-error session of 3 specific affected users — not just the last action.”
• “Build the asof-join the OTHER way: for users who triggered checkout, what % went to error vs success?”
• “Find error fingerprints with NO preceding analytics event in the last 60s. Those are server-internal (cron, webhook).”
• “Find errors where the preceding action distribution is bimodal — multiple distinct repro paths.”