Trend

by Rootly-AI-Labs65832aa6ff7aNo licenseListed Oct 8, 2026Updated Oct 8, 2026

Reliability trend summary for a service, team, or the whole org. Reports incident volume, severity mix, and MTTR direction over a window (default 30 days). Use for standups, 1-on-1s, or quarterly reviews.

AI-generated overview

Summarizes reliability trends for a service, team, or org using Rootly incident data over a 30-day window.

What it does
This skill produces a reliability trend report comparing the last 30 days against the prior 30 days. It pulls incident, uptime, and chart data from Rootly, then computes total incidents, severity mix, MTTR, and repeat incidents. It renders a headline verdict of Improving, Stable, or Degrading along with a metrics table, severity breakdown, top incidents, and flagged observations. It is read-only and never changes Rootly state.
When to use it
Use it for standups, one-on-ones, or quarterly reviews when you need to show whether reliability is getting better or worse. It fits questions about incident volume, severity mix, and MTTR direction for a specific service, a team, or the whole organization.
Requirements
Requires access to Rootly MCP tools (mcprootly*), including listServices, listTeams, listIncidents, and the service or team incident and uptime chart endpoints. No scripts are shipped; it is instructions only.

Reliability Trend

You are summarizing whether things are getting better or worse, scoped to a service, team, or the whole org.

Workflow

1. Determine scope

Parse $ARGUMENTS:

  • Empty or all → org-wide.
  • A name → resolve to a service or team using the same approach as /rootly:lookup:
    1. Try mcp__rootly__listServices first.
    2. Fall back to mcp__rootly__listTeams.
    3. If multiple matches, list the top 5 and ask the user to disambiguate.

2. Pull the chart data

Service scope:

  • Call mcp__rootly__getServiceIncidentsChart for the last 30 days.
  • Call mcp__rootly__getServiceUptimeChart for the same window if available.
  • Call mcp__rootly__listIncidents filtered to the service over the last 30 days (page_size=100) for severity and resolution timing.

Team scope:

  • Call mcp__rootly__getTeamIncidentsChart for the last 30 days.
  • Call mcp__rootly__listIncidents filtered to the team over the last 30 days for severity and MTTR.

Org scope:

  • Call mcp__rootly__listIncidents over the last 30 days (page_size=100, sort=-created_at). If the volume exceeds one page, note the truncation and proceed with a partial picture rather than walking pages.

3. Pull the comparison window

Repeat the same call for the previous 30-day window (days 31–60). This gives a baseline for trend direction.

4. Compute the metrics

For each window, compute:

  • Total incidents
  • Severity mix (count per severity, with critical+high highlighted)
  • MTTR — for resolved incidents only, average resolved_at - started_at. Skip incidents with missing timestamps rather than imputing.
  • Repeat incidents — count of incidents whose service or root cause appears more than once in the window. (Best-effort: if cause data is absent, skip this metric and note it.)

Compare current vs previous to derive trend direction:

  • Improving: incident count down ≥10% AND MTTR not significantly worse.
  • Degrading: incident count up ≥10% OR MTTR up ≥25%.
  • Stable: anything else.

5. Render

## Reliability Trend: [scope name]*30-day window vs prior 30 days*
### Headline**[Improving 📈 / Stable ➡️ / Degrading 📉]** — [one-sentence summary]
### Metrics| Metric | This period | Prior period | Δ ||---|---|---|---|| Total incidents | [N] | [N] | [+/-N (%)] || Critical/High | [N] | [N] | [+/-N] || MTTR | [duration] | [duration] | [+/-duration] || Repeat incidents | [N] | [N] | [+/-N] |
### Severity Mix (this period)- 🔴 Critical: [N]- 🟠 High: [N]- 🟡 Medium: [N]- 🟢 Low: [N]
### Top Incidents (most recent / highest severity)- [INC-XXXX] [title] ([severity], [duration])- [INC-YYYY] [title] ([severity], [duration])[max 5]
### What I'd flag[Concise observations:]- [e.g. "Critical count doubled — both incidents on payments-api in the same week"]- [e.g. "MTTR worsening despite stable volume — investigate response process"]- [e.g. "No incidents this period on this service — expected or coverage gap?"]

6. Read-only

This skill never mutates Rootly state.

7. Error handling

  • If a chart endpoint isn't available for the scope (some MCP versions only support service-level, not team-level), compute metrics manually from listIncidents and proceed.
  • If the prior window has no data, skip the comparison row and label the headline "Insufficient history".
  • If incident count is below 5 in either window, add a caveat: "Sample size is small — trend may not be meaningful."

Source and attribution

Source:Rootly-AI-Labs/rootly-claude-plugininskills/trendat commit65832aa

License: No license

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