perplexity-observability

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

Install

mkdir -p .claude/skills/perplexity-observability && curl -L -o skill.zip "https://mcp.directory/api/skills/download/4784" && unzip -o skill.zip -d .claude/skills/perplexity-observability && rm skill.zip

Installs to .claude/skills/perplexity-observability

About this skill

Perplexity Observability

Overview

Monitor Perplexity Sonar API performance, cost, and quality. Key signals unique to Perplexity: citation count per response (quality indicator), search latency variability (web search is non-deterministic), and per-model cost differences.

Key Metrics

Metricsonar (typical)sonar-pro (typical)Alert Threshold
Latency p501-2s3-5sp95 > 15s
Citations/response3-55-100 for 10min
Error rate<1%<1%>5%
Cost/query$0.005$0.02>$0.10

Prerequisites

  • Perplexity API integration running
  • Metrics backend (Prometheus, Datadog, or custom)
  • Alerting system configured

Instructions

Step 1: Instrument the Perplexity Client

import OpenAI from "openai";

interface SearchMetrics {
  model: string;
  latencyMs: number;
  status: "success" | "error";
  citationCount: number;
  totalTokens: number;
  cached: boolean;
  errorCode?: number;
}

const metrics: SearchMetrics[] = [];

async function instrumentedSearch(
  client: OpenAI,
  query: string,
  model: string = "sonar",
  cached: boolean = false
): Promise<{ response: any; metrics: SearchMetrics }> {
  const start = performance.now();
  let searchMetrics: SearchMetrics;

  try {
    const response = await client.chat.completions.create({
      model,
      messages: [{ role: "user", content: query }],
    });

    searchMetrics = {
      model,
      latencyMs: performance.now() - start,
      status: "success",
      citationCount: (response as any).citations?.length || 0,
      totalTokens: response.usage?.total_tokens || 0,
      cached,
    };

    metrics.push(searchMetrics);
    return { response, metrics: searchMetrics };
  } catch (err: any) {
    searchMetrics = {
      model,
      latencyMs: performance.now() - start,
      status: "error",
      citationCount: 0,
      totalTokens: 0,
      cached,
      errorCode: err.status,
    };

    metrics.push(searchMetrics);
    throw err;
  }
}

Step 2: Prometheus Metrics Export

// Export metrics in Prometheus format
function prometheusMetrics(): string {
  const lines: string[] = [];

  // Latency histogram
  lines.push("# HELP perplexity_latency_ms Search response latency");
  lines.push("# TYPE perplexity_latency_ms histogram");

  // Query counter
  const byModel = metrics.reduce((acc, m) => {
    const key = `${m.model}_${m.status}`;
    acc[key] = (acc[key] || 0) + 1;
    return acc;
  }, {} as Record<string, number>);

  for (const [key, count] of Object.entries(byModel)) {
    const [model, status] = key.split("_");
    lines.push(`perplexity_queries_total{model="${model}",status="${status}"} ${count}`);
  }

  // Citation gauge
  const recentCitations = metrics.slice(-100).filter((m) => m.status === "success");
  const avgCitations = recentCitations.reduce((s, m) => s + m.citationCount, 0) / Math.max(recentCitations.length, 1);
  lines.push(`perplexity_avg_citations ${avgCitations.toFixed(1)}`);

  // Token counter
  const totalTokens = metrics.reduce((s, m) => s + m.totalTokens, 0);
  lines.push(`perplexity_tokens_total ${totalTokens}`);

  return lines.join("\n");
}

Step 3: Citation Quality Scoring

function evaluateCitationQuality(citations: string[]): {
  total: number;
  authoritative: number;
  qualityScore: number;
} {
  const authoritativeTLDs = [".gov", ".edu"];
  const authoritativeDomains = ["wikipedia.org", "arxiv.org", "nature.com", "science.org"];

  let authoritative = 0;
  for (const url of citations) {
    const isAuth = authoritativeTLDs.some((tld) => url.includes(tld)) ||
                   authoritativeDomains.some((d) => url.includes(d));
    if (isAuth) authoritative++;
  }

  return {
    total: citations.length,
    authoritative,
    qualityScore: citations.length > 0 ? authoritative / citations.length : 0,
  };
}

Step 4: Cost Tracking

const COST_PER_MILLION_TOKENS: Record<string, { input: number; output: number }> = {
  "sonar":              { input: 1, output: 1 },
  "sonar-pro":          { input: 3, output: 15 },
  "sonar-reasoning-pro": { input: 3, output: 15 },
  "sonar-deep-research": { input: 2, output: 8 },
};

function estimateCost(model: string, usage: { prompt_tokens: number; completion_tokens: number }): number {
  const rates = COST_PER_MILLION_TOKENS[model] || COST_PER_MILLION_TOKENS["sonar"];
  return (usage.prompt_tokens * rates.input + usage.completion_tokens * rates.output) / 1_000_000;
}

Step 5: Alert Rules (Prometheus/Alertmanager)

groups:
  - name: perplexity
    rules:
      - alert: PerplexityHighLatency
        expr: histogram_quantile(0.95, rate(perplexity_latency_ms_bucket[5m])) > 15000
        for: 5m
        annotations:
          summary: "Perplexity P95 latency exceeds 15 seconds"

      - alert: PerplexityNoCitations
        expr: perplexity_avg_citations == 0
        for: 10m
        annotations:
          summary: "Perplexity returning responses with zero citations"

      - alert: PerplexityHighErrorRate
        expr: rate(perplexity_queries_total{status="error"}[5m]) / rate(perplexity_queries_total[5m]) > 0.05
        for: 5m
        annotations:
          summary: "Perplexity API error rate exceeds 5%"

      - alert: PerplexityCostSpike
        expr: increase(perplexity_tokens_total[1h]) > 1000000
        annotations:
          summary: "Perplexity token usage spike (>1M tokens/hour)"

Dashboard Panels

Track these metrics on your dashboard:

  • Query latency by model (sonar vs sonar-pro histogram)
  • Citations per response distribution
  • Query volume over time (by model)
  • Cost per query trend
  • Error rate by status code (429 vs 500)
  • Cache hit rate

Error Handling

IssueCauseSolution
High latency on sonar-proComplex multi-source searchExpected; use sonar for simple queries
Zero citations alertVague queries or API issueReview query patterns
Cost spikeBurst of sonar-pro queriesCheck for runaway batch jobs
Error rate elevatedRate limiting or API issueCheck for 429s in error breakdown

Output

  • Instrumented Perplexity client with latency/error/citation tracking
  • Prometheus metrics export endpoint
  • Citation quality scoring
  • Cost estimation per query
  • Alert rules for latency, errors, and cost

Resources

Next Steps

For incident response, see perplexity-incident-runbook.

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