fireflies-observability

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Set up comprehensive observability for Fireflies.ai integrations with metrics, traces, and alerts. Use when implementing monitoring for Fireflies.ai operations, setting up dashboards, or configuring alerting for Fireflies.ai integration health. Trigger with phrases like "fireflies monitoring", "fireflies metrics", "fireflies observability", "monitor fireflies", "fireflies alerts", "fireflies tracing".

Install

mkdir -p .claude/skills/fireflies-observability && curl -L -o skill.zip "https://mcp.directory/api/skills/download/8849" && unzip -o skill.zip -d .claude/skills/fireflies-observability && rm skill.zip

Installs to .claude/skills/fireflies-observability

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_quantile on fireflies_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

AlertCauseResponse
API DownFireflies outage or key revokedCheck status page, verify API key
High Error RateSchema change or auth issueInspect error codes in logs
Rate LimitedBurst of requestsEnable request queuing
Webhook BacklogProcessing bottleneckScale 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.

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