From exa-pack
Apply Exa advanced debugging techniques for hard-to-diagnose issues. Use when standard troubleshooting fails, investigating complex race conditions, or preparing evidence bundles for Exa support escalation. Trigger with phrases like "exa hard bug", "exa mystery error", "exa impossible to debug", "difficult exa issue", "exa deep debug".
How this skill is triggered — by the user, by Claude, or both
Slash command
/exa-pack:exa-advanced-troubleshootingThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Deep debugging techniques for complex Exa issues that resist standard troubleshooting.
Deep debugging techniques for complex Exa issues that resist standard troubleshooting.
#!/bin/bash
set -euo pipefail
# advanced-exa-debug.sh
BUNDLE="exa-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=exa-integration --since=1h > "$BUNDLE/logs/pods.log"
journalctl -u exa-service --since "1 hour ago" > "$BUNDLE/logs/system.log"
# 2. Metrics dump
curl -s localhost:9090/api/v1/query?query=exa_requests_total > "$BUNDLE/metrics/requests.json" # 9090: Prometheus port
curl -s localhost:9090/api/v1/query?query=exa_errors_total > "$BUNDLE/metrics/errors.json" # Prometheus port
# 3. Network capture (30 seconds)
timeout 30 tcpdump -i any port 443 -w "$BUNDLE/network/capture.pcap" & # 443: HTTPS port
# 4. Distributed traces
curl -s localhost:16686/api/traces?service=exa > "$BUNDLE/traces/jaeger.json" # 16686: Jaeger UI port
# 5. Configuration state
kubectl get cm exa-config -o yaml > "$BUNDLE/config/configmap.yaml"
kubectl get secret exa-secrets -o yaml > "$BUNDLE/config/secrets-redacted.yaml"
tar -czf "$BUNDLE.tar.gz" "$BUNDLE"
echo "Advanced debug bundle: $BUNDLE.tar.gz"
// Test each layer independently
async function diagnoseExaIssue(): Promise<DiagnosisReport> {
const results: DiagnosisResult[] = [];
// Layer 1: Network connectivity
results.push(await testNetworkConnectivity());
// Layer 2: DNS resolution
results.push(await testDNSResolution('api.exa.com'));
// Layer 3: TLS handshake
results.push(await testTLSHandshake('api.exa.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) };
}
// Strip down to absolute minimum
async function minimalRepro(): Promise<void> {
// 1. Fresh client, no customization
const client = new ExaClient({
apiKey: process.env.EXA_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,
});
}
}
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;
}
}
// Detect memory leaks in Exa 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 # 1024: 1 KB
console.warn('Potential memory leak in exa integration');
}
}
}, 60000); # 60000: 1 minute in ms
// Detect concurrent access issues
class ExaConcurrencyChecker {
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);
}
}
}
## Exa Support Escalation
**Severity:** P[1-4]
**Request ID:** [from error response]
**Timestamp:** [ISO 8601] # 8601 = configured value
### 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 (exa-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]
Run the comprehensive debug script to gather all relevant data.
Test each layer independently to identify the failure point.
Strip down to the simplest failing case.
Use the support template with all collected evidence.
| 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 |
set -euo pipefail
# Test each layer in sequence
curl -v https://api.exa.com/health 2>&1 | grep -E "(Connected|TLS|HTTP)"
For load testing, see exa-load-scale.
npx claudepluginhub p/ktiseos-nyx-exa-pack-plugins-saas-packs-exa-packGuides collaborative design exploration before implementation: explores context, asks clarifying questions, proposes approaches, and writes a design doc for user approval.
Creates structured, bite-sized implementation plans from specs or requirements before writing code. Useful for breaking down multi-step tasks into testable steps with file structure and task boundaries.
Provides Slack GIF creation utilities with dimension/FPS/color constraints and Python PIL-based frame generation. Use for animated Slack emoji or message GIFs.