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Agent Skill · 研究检索

apollo-cost-tuning(阿波罗成本调整)

apollo-cost-tuning 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。

apollo-cost-tuning 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 46,384。

总安装 783周安装 32GitHub Stars 2,077下载 251核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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-cost-tuning(阿波罗成本调整)
来源仓库:https://github.com/jeremylongshore/claude-code-plugins-plus-skills
仓库路径:skills/apollo-cost-tuning
安装命令:
npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill apollo-cost-tuning
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-cost-tuning

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

apollo-cost-tuning 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。它基于 Apollo.io API 的成本模型优化信用使用,区分免费搜索和高成本 enrichment 操作。

使用时需配置 API 密钥并遵循去重、评分和预算跟踪策略,适用于成本控制场景。安装前建议确认权限范围和维护状态,注意是否会触发联网或数据读取操作。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。

来源仓库内路径:skills/apollo-cost-tuning

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skill…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

apollo-cost-tuning 怎么安装?

在终端执行 npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

apollo-cost-tuning 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

apollo-cost-tuning 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

apollo-cost-tuning 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

apollo-cost-tuning 用的人多吗?

公开数据是累计安装 783 次,近一周安装 32 次,下载 251 次,GitHub 2,077 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

apollo-cost-tuning 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 来源仓库有 2,077 星,维护活跃度相对可查。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
apollo-cost-tuning

阿波罗成本调整 · 本页

7832,077接触敏感数据MIT有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Apollo Cost Tuning

Overview

Optimize Apollo.io API costs through credit-aware enrichment. Key cost model: search is free, enrichment costs credits. Apollo charges per unique contact/company lookup. Credits do not roll over. Strategies: deduplicate before enriching, score leads before spending credits, and track daily budget.

Prerequisites

  • Valid Apollo API key
  • Node.js 18+

Instructions

Step 1: Understand Apollo's Credit Model

Action                      | Credits | Notes
----------------------------+---------+-----------------------------------
People Search               | 0       | /mixed_people/api_search (free!)
Organization Search         | 0       | /mixed_companies/search (free!)
People Enrichment (single)  | 1       | /people/match
People Enrichment (bulk)    | 1/match | /people/bulk_match (up to 10/call)
Organization Enrichment     | 1       | /organizations/enrich
Reveal Personal Email       | +1      | reveal_personal_emails param
Reveal Phone Number         | +1      | reveal_phone_number param

Plans (approximate):

  • Free: 50 credits/month
  • Basic: 1,200 credits/month (~$0.04/credit)
  • Professional: 6,000 credits/month
  • Organization: 12,000+ credits/month

Step 2: Track Credit Usage

// src/cost/credit-tracker.ts
class CreditTracker {
  private daily: Map<string, number> = new Map();
  private readonly budget: number;

  constructor(dailyBudget: number = 200) {
    this.budget = dailyBudget;
  }

  record(count: number = 1) {
    const today = new Date().toISOString().split('T')[0];
    this.daily.set(today, (this.daily.get(today) ?? 0) + count);
  }

  todayUsage(): number {
    const today = new Date().toISOString().split('T')[0];
    return this.daily.get(today) ?? 0;
  }

  isOverBudget(): boolean {
    return this.todayUsage() >= this.budget;
  }

  report(): string {
    const used = this.todayUsage();
    return `${used}/${this.budget} credits (${Math.round((used / this.budget) * 100)}%)`;
  }
}

export const creditTracker = new CreditTracker(
  parseInt(process.env.APOLLO_DAILY_CREDIT_BUDGET ?? '200', 10),
);

Step 3: Deduplicate Before Enriching

// src/cost/dedup.ts
import { LRUCache } from 'lru-cache';

// Track enriched contacts to avoid paying twice
const enrichedCache = new LRUCache<string, boolean>({
  max: 50_000,
  ttl: 30 * 24 * 60 * 60 * 1000,  // 30 days
});

export function enrichmentKey(params: { email?: string; linkedin_url?: string;
  first_name?: string; last_name?: string; organization_domain?: string }): string {
  // Prefer email as unique key, fall back to LinkedIn, then name+domain
  return params.email
    ?? params.linkedin_url
    ?? `${params.first_name}:${params.last_name}:${params.organization_domain}`;
}

export function isAlreadyEnriched(key: string): boolean {
  return enrichedCache.has(key);
}

export function markEnriched(key: string) {
  enrichedCache.set(key, true);
}

Step 4: Score Leads Before Enriching

Only spend credits on leads worth contacting.

// src/cost/lead-scorer.ts
interface LeadSignals {
  seniority?: string;
  title?: string;
  companyEmployees?: number;
  hasEmail: boolean;
  hasPhone: boolean;
  hasLinkedIn: boolean;
}

export function shouldEnrich(signals: LeadSignals, threshold: number = 40): boolean {
  let score = 0;

  // Seniority — only enrich decision-makers
  const topSeniority = ['c_suite', 'vp', 'founder', 'owner'];
  if (topSeniority.includes(signals.seniority ?? '')) score += 40;
  else if (signals.seniority === 'director') score += 30;
  else if (signals.seniority === 'manager') score += 15;
  else score += 5;

  // Company size — mid-market is highest value
  if (signals.companyEmployees && signals.companyEmployees >= 50 && signals.companyEmployees <= 1000) score += 25;
  else if (signals.companyEmployees && signals.companyEmployees > 1000) score += 15;

  // Missing data — worth enriching if we need the contact info
  if (!signals.hasEmail) score += 20;
  if (!signals.hasPhone) score += 10;

  return score >= threshold;
}

Step 5: Budget-Aware API Client

// src/cost/budget-client.ts
import axios from 'axios';
import { creditTracker } from './credit-tracker';
import { isAlreadyEnriched, markEnriched, enrichmentKey } from './dedup';

const client = axios.create({
  baseURL: 'https://api.apollo.io/api/v1',
  headers: { 'Content-Type': 'application/json', 'x-api-key': process.env.APOLLO_API_KEY! },
});

// Credit-consuming endpoints
const CREDIT_ENDPOINTS = ['/people/match', '/people/bulk_match', '/organizations/enrich'];

// Block requests when over budget
client.interceptors.request.use((config) => {
  const isCreditEndpoint = CREDIT_ENDPOINTS.some((ep) => config.url?.includes(ep));
  if (isCreditEndpoint && creditTracker.isOverBudget()) {
    throw new Error(`Daily credit budget exceeded (${creditTracker.report()})`);
  }
  return config;
});

// Track credit usage on success
client.interceptors.response.use((response) => {
  const isCreditEndpoint = CREDIT_ENDPOINTS.some((ep) => response.config.url?.includes(ep));
  if (isCreditEndpoint) {
    // Bulk match: count matches, not calls
    const matchCount = response.data?.matches?.length ?? 1;
    creditTracker.record(matchCount);

    // Mark as enriched for dedup
    const email = response.data?.person?.email;
    if (email) markEnriched(email);
  }
  return response;
});

export { client as budgetClient };

Step 6: Cost-Optimized Pipeline

import { budgetClient } from './cost/budget-client';
import { shouldEnrich } from './cost/lead-scorer';
import { isAlreadyEnriched, enrichmentKey } from './cost/dedup';
import { creditTracker } from './cost/credit-tracker';

async function enrichHighValueLeads(people: any[]) {
  let enriched = 0, skipped = 0, deduped = 0;

  const toEnrich: any[] = [];

  for (const person of people) {
    const key = enrichmentKey({ email: person.email, linkedin_url: person.linkedin_url,
      first_name: person.first_name, last_name: person.last_name });

    if (isAlreadyEnriched(key)) { deduped++; continue; }
    if (!shouldEnrich({ seniority: person.seniority, hasEmail: !!person.email,
      hasPhone: false, hasLinkedIn: !!person.linkedin_url })) { skipped++; continue; }

    toEnrich.push(person);
  }

  // Bulk enrich in batches of 10
  for (let i = 0; i < toEnrich.length; i += 10) {
    const batch = toEnrich.slice(i, i + 10);
    await budgetClient.post('/people/bulk_match', {
      details: batch.map((p: any) => ({
        first_name: p.first_name, last_name: p.last_name,
        organization_domain: p.organization?.primary_domain,
      })),
    });
    enriched += batch.length;
  }

  console.log(`Enriched: ${enriched}, Skipped (low-value): ${skipped}, Deduped: ${deduped}`);
  console.log(`Credits: ${creditTracker.report()}`);
}

Output

  • Credit model reference table (free vs paid operations)
  • CreditTracker with daily budget enforcement
  • LRU deduplication preventing double-enrichment charges
  • Lead scoring to enrich only high-value contacts
  • Budget-aware client blocking requests at daily limit
  • Cost-optimized pipeline combining all strategies

Error Handling

IssueResolution
Budget exceededIncrease APOLLO_DAILY_CREDIT_BUDGET or wait until tomorrow
High dedup missesExtend LRU TTL, verify key generation logic
Enriching low-value leadsLower the shouldEnrich threshold
Month-end credit crunchSpread enrichment evenly with daily budgets

Resources

Next Steps

Proceed to apollo-reference-architecture for architecture patterns.

平台分布

Antigravity

94.04%
按下载量换算236

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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