crisis-detector — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited crisis-detector (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.
Identify early warning signs of potential crises before they escalate through pattern recognition, signal monitoring, and risk assessment.
Based on Institute for Crisis Management research and Burson crisis frameworks, combining:
| Claude Does | You Decide |
|---|---|
| Identifies warning signals | Risk tolerance |
| Assesses crisis probability | Response resources |
| Creates detection criteria | Escalation authority |
| Designs monitoring systems | Communication strategy |
| Suggests response triggers | Final action calls |
Crisis Categories:
| Category | Examples | Warning Time |
|---|---|---|
| Operational | Outage, product failure | Hours to days |
| Reputational | Executive scandal, viral complaint | Minutes to hours |
| Legal/Regulatory | Lawsuit, investigation | Days to weeks |
| Financial | Earnings miss, fraud | Hours to days |
| Human | Workplace incident, harassment | Hours to days |
| External | Natural disaster, market crash | Variable |
Signal Types:
| Signal Type | Examples | Monitoring |
|---|---|---|
| Internal | Employee complaints, support tickets | HR, Support data |
| Customer | Review patterns, churn spikes | CX metrics |
| Social | Mention volume, sentiment shift | Social tools |
| Media | Press inquiries, journalist interest | PR inbox |
| Regulatory | Compliance notices, audit findings | Legal |
| Financial | Payment disputes, refund requests | Finance |
Signal Strength Assessment:
| Signal | Weak | Moderate | Strong | Critical |
|---|---|---|---|---|
| Volume spike | +25% | +50% | +100% | +300% |
| Sentiment shift | -10% | -20% | -30% | -50% |
| Media inquiries | 1 | 2-3 | 4-5 | 6+ |
| Support tickets | +10% | +25% | +50% | +100% |
| Social influencer | 10K | 50K | 100K | 500K+ |
Trigger Framework:
| Level | Signals Present | Action |
|---|---|---|
| Watch | 1 moderate signal | Monitor closely |
| Alert | 2+ moderate or 1 strong | Notify team |
| Warning | Multiple strong signals | Assemble team |
| Crisis | Any critical signal | Activate protocol |
Post-Detection Review:
Input:
Design a crisis detection system for:
- E-commerce company (clothing)
- 500K customers
- Active on Instagram, TikTok, Twitter
- Past issue: Shipping delays during holidayOutput:
## Crisis Detection System: E-Commerce Fashion
### Crisis Risk Map
| Crisis Type | Probability | Impact | Priority |
|-------------|-------------|--------|----------|
| Shipping delays | High | High | P1 |
| Product quality issue | Medium | High | P1 |
| Social media backlash | Medium | High | P1 |
| Data breach | Low | Critical | P1 |
| Influencer controversy | Medium | Medium | P2 |
| Supply chain disruption | Medium | High | P2 |
| Payment fraud | Low | Medium | P3 |
---
### Early Warning Signals
#### P1: Shipping Delays
**Leading Indicators (3-5 days before crisis):**
| Signal | Source | Threshold |
|--------|--------|-----------|
| Carrier delay reports | Logistics API | >10% delayed |
| Warehouse backlog | WMS data | >24hr processing |
| Weather events | News/weather | Storm in hub |
| "Where's my order" tickets | Support | +50% daily |
**Lagging Indicators (crisis starting):**
| Signal | Source | Threshold |
|--------|--------|-----------|
| Social mentions | Social listening | "shipping" +100% |
| Review mentions | Trustpilot/G2 | Shipping 3/5 stars |
| Refund requests | Payment system | +30% |
| Chargeback rate | Payment processor | >1% |
---
#### P1: Product Quality Issue
**Leading Indicators:**
| Signal | Source | Threshold |
|--------|--------|-----------|
| Return rate spike | Returns data | >10% on SKU |
| Quality complaints | Support tickets | 3+ same issue |
| Photo complaints | Social | "damaged", "wrong color" |
| Batch-specific issues | QC data | Same lot number |
**Lagging Indicators:**
| Signal | Source | Threshold |
|--------|--------|-----------|
| Viral unboxing | TikTok/Instagram | >10K views negative |
| Review bomb | Product pages | Multiple 1-stars |
| Media inquiry | PR inbox | Journalist question |
---
#### P1: Social Media Backlash
**Leading Indicators:**
| Signal | Source | Threshold |
|--------|--------|-----------|
| Sentiment shift | Social tools | -20% in 24hr |
| Controversial post | Your social | Negative comments >10% |
| Influencer complaint | Social | >50K follower post |
| Screenshot spreading | Twitter/Reddit | Same image 5+ times |
**Lagging Indicators:**
| Signal | Source | Threshold |
|--------|--------|-----------|
| Viral negative | Any platform | >50K engagements |
| Hashtag trending | Twitter | Brand + negative |
| Media pickup | News sites | Article published |
| Competitor amplification | Social | Competitor sharing |
---
### Detection Dashboard
┌──────────────────────────────────────────────────────────┐ │ CRISIS DETECTION DASHBOARD 🟢 NORMAL │ ├──────────────────────────────────────────────────────────┤ │ │ │ SHIPPING STATUS 🟢 Normal │ │ ├─ Carrier delays: 3% (threshold: 10%) │ │ ├─ Backlog: 4 hours (threshold: 24hr) │ │ └─ "Where's my order": 45 (baseline: 50) │ │ │ │ PRODUCT QUALITY 🟢 Normal │ │ ├─ Return rate: 5.2% (threshold: 10%) │ │ ├─ Quality tickets: 2 (threshold: 3+ same) │ │ └─ Photo complaints: 1 (threshold: 5) │ │ │ │ SOCIAL SENTIMENT 🟡 Watch │ │ ├─ Sentiment: -15% (threshold: -20%) │ │ ├─ Volume: +40% (threshold: +50%) │ │ └─ Influencer: None flagged │ │ │ │ SECURITY 🟢 Normal │ │ ├─ Login anomalies: Normal │ │ └─ Payment fraud: 0.3% │ │ │ └──────────────────────────────────────────────────────────┘
---
### Escalation Matrix
| Level | Criteria | Notification | Response |
|-------|----------|--------------|----------|
| 🟢 Normal | All metrics in range | None | Standard ops |
| 🟡 Watch | 1 metric at threshold | Slack alert | Increased monitoring |
| 🟠 Alert | 2+ metrics or 1 exceeded | Team notification | Standby team |
| 🔴 Crisis | Critical threshold breached | All-hands alert | Activate protocol |
---
### Alert Routing
| Signal Type | Primary | Backup | Escalation |
|-------------|---------|--------|------------|
| Shipping | Operations | COO | CEO |
| Product quality | Product | VP Ops | CEO |
| Social media | Marketing | CMO | CEO |
| Security | IT | CTO | CEO + Legal |
| Legal/PR | Legal | CEO | Board |
---
### Holiday Season Adjustments
During high-volume periods (Nov 15 - Dec 31):
| Metric | Normal Threshold | Holiday Threshold |
|--------|------------------|-------------------|
| Carrier delays | 10% | 15% |
| Support volume | +50% | +100% |
| Social volume | +50% | +75% |
| Response time | 4 hours | 8 hours |
**Rationale:** Higher baseline expected; adjust to avoid false alerts
while maintaining genuine crisis detection.Input:
Assess this situation:
- Support tickets up 80% in 2 hours
- Twitter mentions up 150%
- Hashtag #[Brand]Scam trending locally
- 3 refund requests mentioning "charged twice"
- No known system issuesOutput:
## Crisis Assessment: Potential Payment Issue
### Alert Level: 🔴 CRISIS
---
### Signal Analysis
| Signal | Value | Normal | Status |
|--------|-------|--------|--------|
| Support spike | +80% | <25% | CRITICAL |
| Social spike | +150% | <50% | CRITICAL |
| Trending hashtag | Yes | No | CRITICAL |
| Duplicate charge reports | 3 | 0 | CONCERNING |
---
### Probable Cause
**Most likely: Payment processing error**
Evidence:
1. Multiple "charged twice" complaints
2. No known system issues rules out outage
3. Sudden spike suggests batch problem
4. #Scam hashtag = customers think fraud
---
### Immediate Actions
| Priority | Action | Owner | Timeline |
|----------|--------|-------|----------|
| 1 | Check payment processor logs | Engineering | NOW |
| 2 | Identify affected transactions | Finance | 30 min |
| 3 | Prepare holding statement | Comms | 15 min |
| 4 | Alert customer service team | CX Lead | NOW |
| 5 | Monitor hashtag spread | Social | Ongoing |
---
### Holding Statement (Draft)
We're aware some customers may have experienced duplicate charges. Our team is investigating urgently. If you've been affected, please DM us or email [support] - we'll make this right immediately.
Updates to follow shortly.
---
### Escalation Path
**Now:** CTO + CFO + CMO notified
**+30 min:** CEO briefing if not resolved
**+1 hour:** External statement if ongoing
---
### Crisis Trajectory
**If unaddressed (next 2-4 hours):**
- Hashtag goes national
- Media inquiries begin
- Trust pilot review bomb
- Social influencers amplify
**If addressed quickly (next 1-2 hours):**
- Contain to affected customers
- Flip narrative to "responsive company"
- Prevent media escalation
- Build goodwill through fast resolution
---
### Resolution Checklist
- [ ] Root cause identified
- [ ] Affected customers identified
- [ ] Refunds initiated
- [ ] Proactive communication sent
- [ ] Social response deployed
- [ ] Hashtag monitoring active
- [ ] Post-incident review scheduledFollow-up Prompts:
social-listening - Monitoring systemsresponse-coordinator - Crisis responsereputation-recovery - Post-crisis rebuild~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.