Structured patterns and templates for seamless on-call shift handoffs with full context transfer.
Works with
Provides shift handoff document template covering active incidents, ongoing investigations, recent changes, known issues, and upcoming events
Includes recommended 30-minute overlap timing with split responsibilities for outgoing and incoming engineers
Offers quick async handoff template for rapid transitions and mid-incident handoff template for continuity during active incidents
Feat
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionon-call-handoff-patternsExecute the skills CLI command in your project's root directory to begin installation:
Fetches on-call-handoff-patterns from wshobson/agents and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate on-call-handoff-patterns. Access via /on-call-handoff-patterns in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Effective patterns for on-call shift transitions, ensuring continuity, context transfer, and reliable incident response across shifts.
| Component | Purpose |
|---|---|
| Active Incidents | What's currently broken |
| Ongoing Investigations | Issues being debugged |
| Recent Changes | Deployments, configs |
| Known Issues | Workarounds in place |
| Upcoming Events | Maintenance, releases |
Recommended: 30 min overlap between shifts
Outgoing:
├── 15 min: Write handoff document
└── 15 min: Sync call with incoming
Incoming:
├── 15 min: Review handoff document
├── 15 min: Sync call with outgoing
└── 5 min: Verify alerting setup
# On-Call Handoff: Platform Team
**Outgoing**: @alice (2024-01-15 to 2024-01-22)
**Incoming**: @bob (2024-01-22 to 2024-01-29)
**Handoff Time**: 2024-01-22 09:00 UTC
---
## 🔴 Active Incidents
### None currently active
No active incidents at handoff time.
---
## 🟡 Ongoing Investigations
### 1. Intermittent API Timeouts (ENG-1234)
**Status**: Investigating
**Started**: 2024-01-20
**Impact**: ~0.1% of requests timing out
**Context**:
- Timeouts correlate with database backup window (02:00-03:00 UTC)
- Suspect backup process causing lock contention
- Added extra logging in PR #567 (deployed 01/21)
**Next Steps**:
- [ ] Review new logs after tonight's backup
- [ ] Consider moving backup window if confirmed
**Resources**:
- Dashboard: [API Latency](https://grafana/d/api-latency)
- Thread: #platform-eng (01/20, 14:32)
---
### 2. Memory Growth in Auth Service (ENG-1235)
**Status**: Monitoring
**Started**: 2024-01-18
**Impact**: None yet (proactive)
**Context**:
- Memory usage growing ~5% per day
- No memory leak found in profiling
- Suspect connection pool not releasing properly
**Next Steps**:
- [ ] Review heap dump from 01/21
- [ ] Consider restart if usage > 80%
**Resources**:
- Dashboard: [Auth Service Memory](https://grafana/d/auth-memory)
- Analysis doc: [Memory Investigation](https://docs/eng-1235)
---
## 🟢 Resolved This Shift
### Payment Service Outage (2024-01-19)
- **Duration**: 23 minutes
- **Root Cause**: Database connection exhaustion
- **Resolution**: Rolled back v2.3.4, increased pool size
- **Postmortem**: [POSTMORTEM-89](https://docs/postmortem-89)
- **Follow-up tickets**: ENG-1230, ENG-1231
---
## 📋 Recent Changes
### Deployments
| Service | Version | Time | Notes |
| ------------ | ------- | ----------- | -------------------------- |
| api-gateway | v3.2.1 | 01/21 14:00 | Bug fix for header parsing |
| user-service | v2.8.0 | 01/20 10:00 | New profile features |
| auth-service | v4.1.2 | 01/19 16:00 | Security patch |
### Configuration Changes
- 01/21: Increased API rate limit from 1000 to 1500 RPS
- 01/20: Updated database connection pool max from 50 to 75
### Infrastructure
- 01/20: Added 2 nodes to Kubernetes cluster
- 01/19: Upgraded Redis from 6.2 to 7.0
---
## ⚠️ Known Issues & Workarounds
### 1. Slow Dashboard Loading
**Issue**: Grafana dashboards slow on Monday mornings
**Workaround**: Wait 5 min after 08:00 UTC for cache warm-up
**Ticket**: OPS-456 (P3)
### 2. Flaky Integration Test
**Issue**: `test_payment_flow` fails intermittently in CI
**Workaround**: Re-run failed job (usually passes on retry)
**Ticket**: ENG-1200 (P2)
---
## 📅 Upcoming Events
| Date | Event | Impact | Contact |
| ----------- | -------------------- | ------------------- | ------------- |
| 01/23 02:00 | Database maintenance | 5 min read-only | @dba-team |
| 01/24 14:00 | Major release v5.0 | Monitor closely | @release-team |
| 01/25 | Marketing campaign | 2x traffic expected | @platform |
---
## 📞 Escalation Reminders
| Issue Type | First Escalation | Second Escalation |
| --------------- | -------------------- | ----------------- |
| Payment issues | @payments-oncall | @payments-manager |
| Auth issues | @auth-oncall | @security-team |
| Database issues | @dba-team | @infra-manager |
| Unknown/severe | @engineering-manager | @vp-engineering |
---
## 🔧 Quick Reference
### Common Commands
```bashMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
on-call-handoff-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
on-call-handoff-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: on-call-handoff-patterns is the kind of skill you can hand to a new teammate without a long onboarding doc.
on-call-handoff-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in on-call-handoff-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend on-call-handoff-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for on-call-handoff-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
on-call-handoff-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: on-call-handoff-patterns is focused, and the summary matches what you get after install.
on-call-handoff-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.
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