PagerDuty Analytics — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited PagerDuty Analytics (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
PagerDuty Analytics provides data-driven insights into incident response performance. Key metrics include Mean Time to Acknowledge (MTTA), Mean Time to Resolve (MTTR), incident frequency, and responder workload. These metrics help MSPs identify operational bottlenecks, measure SLA compliance, and demonstrate value to clients.
| Metric | Description |
|---|---|
| MTTA | Mean Time to Acknowledge -- average time from incident trigger to first acknowledgement |
| MTTR | Mean Time to Resolve -- average time from incident trigger to resolution |
| MTTE | Mean Time to Engage -- average time from trigger to first responder engagement |
| MTTS | Mean Time to Start -- average time from trigger to first status change |
| Incident Count | Total number of incidents in the time period |
| Interruptions | Number of off-hours notifications that interrupted responders |
Analytics can be aggregated at different levels:
All analytics queries require a time range:
since -- Start of the analysis period (ISO 8601)until -- End of the analysis period (ISO 8601)pagerduty_get_analytics_incidentsParameters:
since -- Start of date range (ISO 8601)until -- End of date range (ISO 8601)urgency -- Filter by urgency (high, low)service_ids[] -- Filter by serviceteam_ids[] -- Filter by teamExample response:
{
"data": {
"mean_seconds_to_acknowledge": 180,
"mean_seconds_to_resolve": 3600,
"mean_seconds_to_engage": 120,
"mean_seconds_to_first_ack": 180,
"mean_seconds_to_mobilize": 300,
"total_incident_count": 42,
"total_interruptions": 8,
"up_time_pct": 99.5
},
"filters": {
"since": "2026-03-01T00:00:00Z",
"until": "2026-03-27T00:00:00Z"
}
}pagerduty_get_analytics_servicesParameters:
since -- Start of date range (ISO 8601)until -- End of date range (ISO 8601)service_ids[] -- Filter to specific servicesExample response:
{
"data": [
{
"service_id": "PSVC123",
"service_name": "Payment API",
"mean_seconds_to_acknowledge": 120,
"mean_seconds_to_resolve": 2400,
"total_incident_count": 15,
"total_interruptions": 3,
"up_time_pct": 99.8
},
{
"service_id": "PSVC456",
"service_name": "Auth Service",
"mean_seconds_to_acknowledge": 300,
"mean_seconds_to_resolve": 7200,
"total_incident_count": 27,
"total_interruptions": 5,
"up_time_pct": 98.9
}
]
}pagerduty_get_analytics_incidents for the past monthpagerduty_get_analytics_services to break down by servicetotal_incident_count descending to find noisiest servicesmean_seconds_to_resolve to find slowest-to-resolve servicestotal_interruptions to measure off-hours impact| MTTA | Assessment |
|---|---|
| < 1 min | Excellent -- likely automated acknowledgement |
| 1-5 min | Good -- responders are engaged |
| 5-15 min | Acceptable -- room for improvement |
| 15-30 min | Needs attention -- review notification rules |
| > 30 min | Critical -- escalation policies may not be working |
| MTTR | Assessment |
|---|---|
| < 30 min | Excellent -- fast resolution |
| 30 min - 2 hr | Good -- effective incident response |
| 2-4 hr | Acceptable for complex issues |
| 4-8 hr | Needs review -- investigate bottlenecks |
| > 8 hr | Critical -- consider runbooks and automation |
Cause: No incidents in the requested time range Solution: Expand the time range or remove filters
Cause: Exceeded 60 requests per minute for analytics endpoints Solution: Cache results and reduce query frequency; use broader time ranges
Cause: Requested time range exceeds the maximum (typically 6 months) Solution: Break the query into smaller time windows
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.