+ "description": "Find events dropped before they were stored in Sentry — ground-truth data-fidelity information about what was and wasn't captured.\n\nEvents can be dropped client-side in the SDK (sample_rate, before_send) or\nserver-side at ingest (rate limited, over quota, filtered, invalid, abuse/spike\nprotection, cardinality limited). Accepted-only views (searches, aggregates,\ncharts) can't show this, so the data may be incomplete in ways they don't reveal\n— for example, a flat or spiky chart caused entirely by drops.\n\nUse this tool when you need to:\n- Explain why a chart is flat, lower than expected, or doesn't match what the user is sending\n- Confirm the data you need is actually in Sentry (not dropped) before trusting a query, aggregate, or dashboard\n- Attribute a volume anomaly to a specific drop reason (quota, spike protection, sampling, filters)\n- Tell the user why their data is missing and what to do about it (raise quota, fix sampling, etc.)\n\nReturns dropped event volume bucketed over time, with the drop `outcome` and `reason`\nfor each bucket, plus the accepted volume per bucket so you can compute the dropped share.\n\n<examples>\nfind_dropped_events(organizationSlug='my-org', dataset='spans', projectSlug='my-project')\nfind_dropped_events(organizationSlug='my-org', dataset='logs', statsPeriod='30d')\nfind_dropped_events(organizationSlug='my-org', dataset='errors', outcome='rate_limited')\n</examples>\n\n<hints>\n- This is independent of any search query — it reports drops for the whole project/time range.\n- `outcome` is the drop kind (e.g. rate_limited, filtered); `reason` is the sub-cause (e.g. key_quota, sample_rate).\n- Pass `outcome` and/or `reason` to scope the dropped side to one classification; the accepted volume is always returned in full.\n- An empty `droppedEvents` list means no drops in the window — the data can be trusted.\n</hints>",
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