fireflies-observability
Configures observability tools like Prometheus and Grafana for Fireflies.ai API tracking.
Install
mkdir -p .claude/skills/fireflies-observability && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/8849" && unzip -o skill.zip -d .claude/skills/fireflies-observability && rm skill.zipInstalls to .claude/skills/fireflies-observability
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Monitor Fireflies.ai integration health with metrics, alerts, and dashboards.Key capabilities
- →Instrument GraphQL clients for request latency and error tracking
- →Monitor webhook event processing and queue depth
- →Execute periodic health check probes
- →Track seat utilization and transcript counts per user
- →Configure Prometheus alerting rules for integration health
How it works
It instruments code with Prometheus client libraries to track API performance and webhook processing, while providing alerting rules to monitor system health.
Inputs & outputs
When to use fireflies-observability
- →Track Fireflies API request latency
- →Set up alerts for webhook failures
- →Monitor transcript processing reliability
- →Visualize API seat utilization in Grafana
About this skill
Fireflies.ai Observability
Overview
Monitor Fireflies.ai integration health: API connectivity, webhook delivery, transcript processing latency, and seat utilization. Built for Prometheus/Grafana but adaptable to any metrics system.
Prerequisites
- Fireflies Business+ plan (for full API access)
- Prometheus + Grafana (or equivalent metrics stack)
- Webhook endpoint deployed and receiving events
Instructions
Step 1: Instrument the GraphQL Client
// lib/fireflies-instrumented.ts
import { Counter, Histogram, Gauge } from "prom-client";
const apiRequests = new Counter({
name: "fireflies_api_requests_total",
help: "Total Fireflies API requests",
labelNames: ["operation", "status"],
});
const apiLatency = new Histogram({
name: "fireflies_api_latency_seconds",
help: "Fireflies API request latency",
labelNames: ["operation"],
buckets: [0.1, 0.25, 0.5, 1, 2, 5, 10],
});
const FIREFLIES_API = "https://api.fireflies.ai/graphql";
export async function firefliesQueryInstrumented(
operation: string,
query: string,
variables?: any
) {
const timer = apiLatency.startTimer({ operation });
try {
const res = await fetch(FIREFLIES_API, {
method: "POST",
headers: {
"Content-Type": "application/json",
Authorization: `Bearer ${process.env.FIREFLIES_API_KEY}`,
},
body: JSON.stringify({ query, variables }),
});
const json = await res.json();
if (json.errors) {
apiRequests.inc({ operation, status: json.errors[0].code || "error" });
throw new Error(json.errors[0].message);
}
apiRequests.inc({ operation, status: "success" });
return json.data;
} catch (err) {
apiRequests.inc({ operation, status: "failure" });
throw err;
} finally {
timer();
}
}
Step 2: Webhook Event Metrics
const webhookEvents = new Counter({
name: "fireflies_webhook_events_total",
help: "Webhook events received",
labelNames: ["event_type", "status"],
});
const webhookProcessingTime = new Histogram({
name: "fireflies_webhook_processing_seconds",
help: "Time to process webhook events",
buckets: [0.1, 0.5, 1, 5, 10, 30],
});
const transcriptQueue = new Gauge({
name: "fireflies_transcript_queue_depth",
help: "Number of transcripts queued for processing",
});
export async function handleWebhookWithMetrics(event: any) {
const timer = webhookProcessingTime.startTimer();
transcriptQueue.inc();
try {
await processTranscriptReady(event.meetingId);
webhookEvents.inc({ event_type: event.eventType, status: "success" });
} catch (err) {
webhookEvents.inc({ event_type: event.eventType, status: "error" });
throw err;
} finally {
timer();
transcriptQueue.dec();
}
}
Step 3: Health Check Probe
const healthStatus = new Gauge({
name: "fireflies_health_status",
help: "Fireflies API health (1=healthy, 0=unhealthy)",
});
// Run every 5 minutes
async function healthProbe() {
try {
const start = Date.now();
const data = await firefliesQueryInstrumented("health_check", "{ user { email } }");
const latencyMs = Date.now() - start;
healthStatus.set(1);
console.log(`Fireflies health: OK (${latencyMs}ms)`);
} catch (err) {
healthStatus.set(0);
console.error(`Fireflies health: FAILED - ${(err as Error).message}`);
}
}
setInterval(healthProbe, 5 * 60 * 1000);
Step 4: Seat Utilization Tracking
const seatUtilization = new Gauge({
name: "fireflies_seat_utilization",
help: "Transcripts per user",
labelNames: ["user_email"],
});
const totalSeats = new Gauge({
name: "fireflies_total_seats",
help: "Total Fireflies seats",
});
// Run daily
async function trackSeatUtilization() {
const data = await firefliesQueryInstrumented("seat_audit", `{
users { email num_transcripts }
}`);
totalSeats.set(data.users.length);
for (const user of data.users) {
seatUtilization.set({ user_email: user.email }, user.num_transcripts);
}
const inactive = data.users.filter((u: any) => u.num_transcripts < 2);
if (inactive.length > 3) {
console.warn(`${inactive.length} seats with <2 transcripts -- review for cost savings`);
}
}
Step 5: Alerting Rules
# prometheus/rules/fireflies.yml
groups:
- name: fireflies
rules:
- alert: FirefliesAPIDown
expr: fireflies_health_status == 0
for: 10m
labels:
severity: critical
annotations:
summary: "Fireflies API unreachable for 10+ minutes"
- alert: FirefliesHighErrorRate
expr: rate(fireflies_api_requests_total{status!="success"}[5m]) > 0.1
for: 5m
labels:
severity: warning
annotations:
summary: "Fireflies API error rate >10% over 5 minutes"
- alert: FirefliesRateLimited
expr: rate(fireflies_api_requests_total{status="too_many_requests"}[5m]) > 0
labels:
severity: warning
annotations:
summary: "Fireflies API rate limiting detected"
- alert: FirefliesWebhookBacklog
expr: fireflies_transcript_queue_depth > 50
for: 15m
labels:
severity: warning
annotations:
summary: "Webhook processing backlog exceeds 50 transcripts"
- alert: FirefliesSlowProcessing
expr: histogram_quantile(0.95, rate(fireflies_webhook_processing_seconds_bucket[1h])) > 30
labels:
severity: warning
annotations:
summary: "Webhook processing P95 exceeds 30 seconds"
Step 6: Dashboard Panels (Grafana)
Key panels to create:
- API Health:
fireflies_health_status(stat panel, green/red) - Request Rate:
rate(fireflies_api_requests_total[5m])by status - Latency P50/P95/P99:
histogram_quantileonfireflies_api_latency_seconds - Webhook Events/Hour:
increase(fireflies_webhook_events_total[1h]) - Queue Depth:
fireflies_transcript_queue_depth(gauge) - Seat Utilization:
fireflies_seat_utilization(table, sorted ascending)
Error Handling
| Alert | Cause | Response |
|---|---|---|
| API Down | Fireflies outage or key revoked | Check status page, verify API key |
| High Error Rate | Schema change or auth issue | Inspect error codes in logs |
| Rate Limited | Burst of requests | Enable request queuing |
| Webhook Backlog | Processing bottleneck | Scale webhook workers |
Output
- Instrumented GraphQL client with latency and error metrics
- Webhook event tracking with queue depth monitoring
- Health probe running on 5-minute interval
- Prometheus alerting rules for critical conditions
Resources
Next Steps
For incident response, see fireflies-incident-runbook.
When not to use it
- →Real-time incident response
- →Direct modification of Fireflies.ai account settings
Prerequisites
Limitations
- →Requires Fireflies Business+ plan for full API access
- →Alerting rules assume Prometheus/Grafana stack
How it compares
It provides pre-built instrumentation patterns and alerting rules instead of requiring manual setup of monitoring logic.
Compared to similar skills
fireflies-observability side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| fireflies-observability (this skill) | 0 | 27d | Caution | Advanced |
| langfuse | 7 | 6mo | No flags | Intermediate |
| appinsights-instrumentation | 6 | 7mo | Review | Beginner |
| instantly-observability | 2 | 27d | Caution | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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