home / skills / jeremylongshore / claude-code-plugins-plus-skills / replit-advanced-troubleshooting
/plugins/saas-packs/replit-pack/skills/replit-advanced-troubleshooting
This skill helps you diagnose hard to debug Replit issues by guiding advanced troubleshooting, evidence collection, and structured escalation workflows.
npx playbooks add skill jeremylongshore/claude-code-plugins-plus-skills --skill replit-advanced-troubleshootingReview the files below or copy the command above to add this skill to your agents.
---
name: replit-advanced-troubleshooting
description: |
Apply Replit advanced debugging techniques for hard-to-diagnose issues.
Use when standard troubleshooting fails, investigating complex race conditions,
or preparing evidence bundles for Replit support escalation.
Trigger with phrases like "replit hard bug", "replit mystery error",
"replit impossible to debug", "difficult replit issue", "replit deep debug".
allowed-tools: Read, Grep, Bash(kubectl:*), Bash(curl:*), Bash(tcpdump:*)
version: 1.0.0
license: MIT
author: Jeremy Longshore <[email protected]>
---
# Replit Advanced Troubleshooting
## Overview
Deep debugging techniques for complex Replit issues that resist standard troubleshooting.
## Prerequisites
- Access to production logs and metrics
- kubectl access to clusters
- Network capture tools available
- Understanding of distributed tracing
## Evidence Collection Framework
### Comprehensive Debug Bundle
```bash
#!/bin/bash
# advanced-replit-debug.sh
BUNDLE="replit-advanced-debug-$(date +%Y%m%d-%H%M%S)"
mkdir -p "$BUNDLE"/{logs,metrics,network,config,traces}
# 1. Extended logs (1 hour window)
kubectl logs -l app=replit-integration --since=1h > "$BUNDLE/logs/pods.log"
journalctl -u replit-service --since "1 hour ago" > "$BUNDLE/logs/system.log"
# 2. Metrics dump
curl -s localhost:9090/api/v1/query?query=replit_requests_total > "$BUNDLE/metrics/requests.json"
curl -s localhost:9090/api/v1/query?query=replit_errors_total > "$BUNDLE/metrics/errors.json"
# 3. Network capture (30 seconds)
timeout 30 tcpdump -i any port 443 -w "$BUNDLE/network/capture.pcap" &
# 4. Distributed traces
curl -s localhost:16686/api/traces?service=replit > "$BUNDLE/traces/jaeger.json"
# 5. Configuration state
kubectl get cm replit-config -o yaml > "$BUNDLE/config/configmap.yaml"
kubectl get secret replit-secrets -o yaml > "$BUNDLE/config/secrets-redacted.yaml"
tar -czf "$BUNDLE.tar.gz" "$BUNDLE"
echo "Advanced debug bundle: $BUNDLE.tar.gz"
```
## Systematic Isolation
### Layer-by-Layer Testing
```typescript
// Test each layer independently
async function diagnoseReplitIssue(): Promise<DiagnosisReport> {
const results: DiagnosisResult[] = [];
// Layer 1: Network connectivity
results.push(await testNetworkConnectivity());
// Layer 2: DNS resolution
results.push(await testDNSResolution('api.replit.com'));
// Layer 3: TLS handshake
results.push(await testTLSHandshake('api.replit.com'));
// Layer 4: Authentication
results.push(await testAuthentication());
// Layer 5: API response
results.push(await testAPIResponse());
// Layer 6: Response parsing
results.push(await testResponseParsing());
return { results, firstFailure: results.find(r => !r.success) };
}
```
### Minimal Reproduction
```typescript
// Strip down to absolute minimum
async function minimalRepro(): Promise<void> {
// 1. Fresh client, no customization
const client = new ReplitClient({
apiKey: process.env.REPLIT_API_KEY!,
});
// 2. Simplest possible call
try {
const result = await client.ping();
console.log('Ping successful:', result);
} catch (error) {
console.error('Ping failed:', {
message: error.message,
code: error.code,
stack: error.stack,
});
}
}
```
## Timing Analysis
```typescript
class TimingAnalyzer {
private timings: Map<string, number[]> = new Map();
async measure<T>(label: string, fn: () => Promise<T>): Promise<T> {
const start = performance.now();
try {
return await fn();
} finally {
const duration = performance.now() - start;
const existing = this.timings.get(label) || [];
existing.push(duration);
this.timings.set(label, existing);
}
}
report(): TimingReport {
const report: TimingReport = {};
for (const [label, times] of this.timings) {
report[label] = {
count: times.length,
min: Math.min(...times),
max: Math.max(...times),
avg: times.reduce((a, b) => a + b, 0) / times.length,
p95: this.percentile(times, 95),
};
}
return report;
}
}
```
## Memory and Resource Analysis
```typescript
// Detect memory leaks in Replit client usage
const heapUsed: number[] = [];
setInterval(() => {
const usage = process.memoryUsage();
heapUsed.push(usage.heapUsed);
// Alert on sustained growth
if (heapUsed.length > 60) { // 1 hour at 1/min
const trend = heapUsed[59] - heapUsed[0];
if (trend > 100 * 1024 * 1024) { // 100MB growth
console.warn('Potential memory leak in replit integration');
}
}
}, 60000);
```
## Race Condition Detection
```typescript
// Detect concurrent access issues
class ReplitConcurrencyChecker {
private inProgress: Set<string> = new Set();
async execute<T>(key: string, fn: () => Promise<T>): Promise<T> {
if (this.inProgress.has(key)) {
console.warn(`Concurrent access detected for ${key}`);
}
this.inProgress.add(key);
try {
return await fn();
} finally {
this.inProgress.delete(key);
}
}
}
```
## Support Escalation Template
```markdown
## Replit Support Escalation
**Severity:** P[1-4]
**Request ID:** [from error response]
**Timestamp:** [ISO 8601]
### Issue Summary
[One paragraph description]
### Steps to Reproduce
1. [Step 1]
2. [Step 2]
### Expected vs Actual
- Expected: [behavior]
- Actual: [behavior]
### Evidence Attached
- [ ] Debug bundle (replit-advanced-debug-*.tar.gz)
- [ ] Minimal reproduction code
- [ ] Timing analysis
- [ ] Network capture (if relevant)
### Workarounds Attempted
1. [Workaround 1] - Result: [outcome]
2. [Workaround 2] - Result: [outcome]
```
## Instructions
### Step 1: Collect Evidence Bundle
Run the comprehensive debug script to gather all relevant data.
### Step 2: Systematic Isolation
Test each layer independently to identify the failure point.
### Step 3: Create Minimal Reproduction
Strip down to the simplest failing case.
### Step 4: Escalate with Evidence
Use the support template with all collected evidence.
## Output
- Comprehensive debug bundle collected
- Failure layer identified
- Minimal reproduction created
- Support escalation submitted
## Error Handling
| Issue | Cause | Solution |
|-------|-------|----------|
| Can't reproduce | Race condition | Add timing analysis |
| Intermittent failure | Timing-dependent | Increase sample size |
| No useful logs | Missing instrumentation | Add debug logging |
| Memory growth | Resource leak | Use heap profiling |
## Examples
### Quick Layer Test
```bash
# Test each layer in sequence
curl -v https://api.replit.com/health 2>&1 | grep -E "(Connected|TLS|HTTP)"
```
## Resources
- [Replit Support Portal](https://support.replit.com)
- [Replit Status Page](https://status.replit.com)
## Next Steps
For load testing, see `replit-load-scale`.This skill applies advanced Replit debugging techniques for hard-to-diagnose issues that resist standard troubleshooting. It provides a repeatable evidence-collection framework, layer-by-layer isolation checks, timing and memory analysis, and a support escalation template. Use it to produce a compact, actionable debug bundle and a clear reproduction for support teams. The goal is to shorten time-to-resolution for intermittent, racey, or resource-related failures.
The skill automates comprehensive evidence collection: extended logs, metrics, network captures, distributed traces, and redacted configuration. It guides systematic isolation by testing network, DNS, TLS, auth, API responses, and parsing independently, then creating a minimal reproduction. It adds timing and memory instrumentation to surface latency patterns, leaks, and concurrency conflicts, and formats everything into a support-ready escalation package.
What should I include in the debug bundle?
Include extended pod and system logs, metrics queries, a short network pcap, distributed traces, and redacted config and secrets. Timestamp everything.
How do I catch race conditions?
Use concurrency checkers and timing analysis, increase sampling frequency, and create a minimal repro that stresses concurrent paths.