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apollo-observability阿波罗可观测性

Agent Skill

apollo-observability 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

710

周安装

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下载量

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:apollo-observability(阿波罗可观测性)
来源仓库:https://github.com/jeremylongshore/claude-code-plugins-plus-skills
仓库路径:skills/apollo-observability
安装命令:
npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill apollo-observability
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill apollo-observability

简介

apollo-observability 提供 Apollo.io 集成的可观测性方案,包括 Prometheus 指标、结构化日志和 OpenTelemetry 追踪。

  • 覆盖信用消耗率、丰富化成功率等关键指标监控,支持告警规则设置与 PII 脱敏处理。
  • 适用于生产环境集成健康度分析,帮助识别性能瓶颈与异常行为,提升系统可靠性。
  • 使用前需有效 API 密钥,并确认是否会整理敏感数据或暴露内部调用链路。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Apollo Observability

Overview

Comprehensive observability for Apollo.io integrations: Prometheus metrics (request count, latency, rate limits, credits), structured logging with PII redaction, OpenTelemetry tracing, and alerting rules. Tracks the metrics that matter: credit burn rate, enrichment success rate, and API health.

Prerequisites

  • Valid Apollo API key
  • Node.js 18+

Instructions

Step 1: Prometheus Metrics

// src/observability/metrics.ts
import { Counter, Histogram, Gauge, Registry } from 'prom-client';

export const registry = new Registry();

export const requestsTotal = new Counter({
  name: 'apollo_requests_total',
  help: 'Total Apollo API requests by endpoint and status',
  labelNames: ['endpoint', 'method', 'status'] as const,
  registers: [registry],
});

export const requestDuration = new Histogram({
  name: 'apollo_request_duration_seconds',
  help: 'Apollo API request duration',
  labelNames: ['endpoint'] as const,
  buckets: [0.1, 0.25, 0.5, 1, 2.5, 5, 10],
  registers: [registry],
});

export const rateLimitRemaining = new Gauge({
  name: 'apollo_rate_limit_remaining',
  help: 'Remaining requests in current rate limit window',
  labelNames: ['endpoint'] as const,
  registers: [registry],
});

export const creditsUsed = new Counter({
  name: 'apollo_credits_used_total',
  help: 'Total Apollo enrichment credits consumed',
  labelNames: ['type'] as const,  // 'person', 'organization', 'bulk'
  registers: [registry],
});

export const enrichmentSuccessRate = new Gauge({
  name: 'apollo_enrichment_success_rate',
  help: 'Percentage of enrichment calls that found a match',
  registers: [registry],
});

Step 2: Axios Interceptors for Auto-Collection

// src/observability/instrument.ts
import { AxiosInstance } from 'axios';
import { requestsTotal, requestDuration, rateLimitRemaining, creditsUsed } from './metrics';

const CREDIT_ENDPOINTS = ['/people/match', '/people/bulk_match', '/organizations/enrich'];

export function instrumentClient(client: AxiosInstance) {
  client.interceptors.request.use((config) => {
    (config as any)._startTime = Date.now();
    return config;
  });

  client.interceptors.response.use(
    (response) => {
      const endpoint = response.config.url ?? 'unknown';
      const duration = (Date.now() - (response.config as any)._startTime) / 1000;

      requestsTotal.inc({ endpoint, method: response.config.method?.toUpperCase() ?? 'GET', status: String(response.status) });
      requestDuration.observe({ endpoint }, duration);

      // Rate limit tracking
      const remaining = response.headers['x-rate-limit-remaining'];
      if (remaining) rateLimitRemaining.set({ endpoint }, parseInt(remaining, 10));

      // Credit tracking
      if (CREDIT_ENDPOINTS.some((ep) => endpoint.includes(ep))) {
        const type = endpoint.includes('bulk') ? 'bulk' : endpoint.includes('organization') ? 'organization' : 'person';
        const count = response.data?.matches?.length ?? 1;
        creditsUsed.inc({ type }, count);
      }

      return response;
    },
    (err) => {
      requestsTotal.inc({
        endpoint: err.config?.url ?? 'unknown',
        method: err.config?.method?.toUpperCase() ?? 'GET',
        status: String(err.response?.status ?? 0),
      });
      return Promise.reject(err);
    },
  );
}

Step 3: Structured Logging with PII Redaction

// src/observability/logger.ts
import pino from 'pino';

export const logger = pino({
  level: process.env.LOG_LEVEL ?? 'info',
  redact: {
    paths: ['*.email', '*.phone_numbers', '*.linkedin_url', 'headers.x-api-key'],
    censor: '[REDACTED]',
  },
  formatters: { level: (label) => ({ level: label }) },
  transport: process.env.NODE_ENV !== 'production' ? { target: 'pino-pretty' } : undefined,
});

export const apolloLog = logger.child({ service: 'apollo' });

// Usage:
// apolloLog.info({ endpoint: '/mixed_people/api_search', results: 25 }, 'Search completed');
// apolloLog.warn({ endpoint: '/people/match', status: 429 }, 'Rate limited');
// apolloLog.error({ err, endpoint: '/contacts' }, 'Request failed');

Step 4: OpenTelemetry Tracing

// src/observability/tracing.ts
import { trace, SpanStatusCode } from '@opentelemetry/api';
import { AxiosInstance } from 'axios';

const tracer = trace.getTracer('apollo-integration');

export function addTracing(client: AxiosInstance) {
  client.interceptors.request.use((config) => {
    const span = tracer.startSpan(`apollo.${config.method?.toUpperCase()} ${config.url}`);
    span.setAttribute('apollo.endpoint', config.url ?? '');
    (config as any)._span = span;
    return config;
  });

  client.interceptors.response.use(
    (response) => {
      const span = (response.config as any)._span;
      if (span) {
        span.setAttribute('http.status_code', response.status);
        span.setAttribute('apollo.rate_limit_remaining', response.headers['x-rate-limit-remaining'] ?? 'unknown');
        span.setStatus({ code: SpanStatusCode.OK });
        span.end();
      }
      return response;
    },
    (err) => {
      const span = (err.config as any)?._span;
      if (span) {
        span.setAttribute('http.status_code', err.response?.status ?? 0);
        span.setStatus({ code: SpanStatusCode.ERROR, message: err.message });
        span.end();
      }
      return Promise.reject(err);
    },
  );
}

Step 5: Alerting Rules

# prometheus/apollo-alerts.yml
groups:
  - name: apollo-integration
    rules:
      - alert: ApolloHighErrorRate
        expr: rate(apollo_requests_total{status=~"4..|5.."}[5m]) / rate(apollo_requests_total[5m]) > 0.1
        for: 5m
        labels: { severity: critical }
        annotations: { summary: "Apollo API error rate > 10% for 5 minutes" }

      - alert: ApolloRateLimitLow
        expr: apollo_rate_limit_remaining < 20
        for: 1m
        labels: { severity: warning }
        annotations: { summary: "Apollo rate limit below 20 remaining requests" }

      - alert: ApolloHighLatency
        expr: histogram_quantile(0.95, rate(apollo_request_duration_seconds_bucket[5m])) > 5
        for: 10m
        labels: { severity: warning }
        annotations: { summary: "Apollo p95 latency > 5s for 10 minutes" }

      - alert: ApolloCreditBurnRate
        expr: rate(apollo_credits_used_total[1h]) * 24 > 500
        for: 30m
        labels: { severity: warning }
        annotations: { summary: "Apollo credit burn rate projects > 500/day" }

Step 6: Metrics Endpoint

import express from 'express';
import { registry } from './metrics';

const metricsApp = express();
metricsApp.get('/metrics', async (_, res) => {
  res.set('Content-Type', registry.contentType);
  res.end(await registry.metrics());
});
metricsApp.get('/health', (_, res) => res.json({ status: 'ok' }));
metricsApp.listen(9090, () => console.log('Metrics on :9090'));

Output

  • Prometheus metrics: requests, duration, rate limits, credits, enrichment success
  • Axios interceptors for automatic collection on every API call
  • Pino structured logger with PII redaction
  • OpenTelemetry tracing spans for distributed tracing
  • Alerting rules for errors, rate limits, latency, and credit burn rate
  • /metrics and /health HTTP endpoints

Error Handling

IssueResolution
Missing metricsVerify instrumentClient() called before first API call
Alert noiseTune for duration and thresholds
Log volumeUse LOG_LEVEL=warn in production
Credit burn alertReview enrichment scoring thresholds in apollo-cost-tuning

Resources

Next Steps

Proceed to apollo-incident-runbook for incident response.

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