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Agent Skill · 研究检索

ads-budget(广告预算)

ads-budget 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。

ads-budget 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,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 13,970。

总安装 8,938周安装 380GitHub Stars 3,730下载 3,131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
unknown

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:ads-budget(广告预算)
来源仓库:https://github.com/agricidaniel/claude-ads
仓库路径:skills/ads-budget
安装命令:
npx skills add https://github.com/agricidaniel/claude-ads --skill ads-budget
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/agricidaniel/claude-ads --skill ads-budget

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。

用于优化广告预算分配与出价策略,基于历史表现数据提供增投或暂停建议。采用 70/20/10 分配框架,结合 CPC/CPA 基准与健康评分判断渠道优先级。需输入至少 14 天的花费数据,确保 kill/scale 决策有足够统计支撑。

安装命令为 npx skills add https://github.com/agricidaniel/claude-ads --skill ads-budget,建议核验数据周期与平台覆盖完整性。ads-budget 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/ads-budget

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/agricidaniel/claude-ads --skill ads-budget;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

ads-budget 怎么安装?

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

ads-budget 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。

ads-budget 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

ads-budget 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

ads-budget 用的人多吗?

公开数据是累计安装 8,938 次,近一周安装 380 次,下载 3,131 次,GitHub 3,730 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。

ads-budget 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 3,730 星,维护活跃度相对可查。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 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
ads-budget

广告预算 · 本页

8,9383,730只读未明确通过

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

Budget Allocation & Bidding Strategy

Process

  1. Collect budget and performance data across all active platforms
  2. Read ads/references/budget-allocation.md for allocation framework
  3. Read ads/references/bidding-strategies.md for strategy decision trees
  4. Read ads/references/benchmarks.md for CPC/CPA benchmarks
  5. Read ads/references/scoring-system.md for health score algorithm
  6. Validate: confirm spend data covers ≥14 days before evaluating kill/scale decisions
  7. Evaluate budget allocation, bidding strategy, and scaling readiness
  8. Validate: verify kill list candidates have sufficient data (≥20 clicks or ≥$100 spend) before recommending pause
  9. Generate recommendations with kill list and scale list

Budget Allocation Framework

70/20/10 Rule

  • 70% on proven channels (consistent ROAS/CPA targets met)
  • 20% on scaling channels (showing promise, need more data)
  • 10% on testing channels (new platforms, audiences, creatives)

Platform Selection Matrix

Business TypePrimarySecondaryTesting
SaaS B2BGoogle Search, LinkedInMeta, YouTubeTikTok, Microsoft
E-commerceGoogle Shopping, MetaTikTok, YouTubeMicrosoft, LinkedIn
Local ServiceGoogle Search, Google LSAMetaMicrosoft, YouTube
B2B EnterpriseLinkedIn, Google SearchMetaMicrosoft, TikTok
Info ProductsMeta, YouTubeGoogle SearchTikTok
Mobile AppMeta, Google UACTikTokApple Ads
Real EstateGoogle Search, MetaYouTubeMicrosoft
HealthcareGoogle SearchMetaMicrosoft, YouTube
FinanceGoogle Search, MetaLinkedInMicrosoft
Agency (clients)Varies by clientN/AN/A

Budget Sufficiency Rules

PlatformMinimum DailyLearning Phase Budget
Google Search$20/daySufficient for 15+ conv/month
Google PMax$50/daySufficient for algorithm optimization
Meta$20/day per ad set≥5x target CPA per ad set
LinkedIn$50/day Sponsored Content15+ conversions/month
TikTok$50/day campaign, $20/day ad group≥50x target CPA per ad group
MicrosoftNo strict minimumSufficient for stable delivery

Bidding Strategy Evaluation

Google Ads Bidding Decision Tree

Start
├─ <30 conversions/month?
│  └─ Use Maximize Clicks (cap CPC at benchmark)
│     └─ When >30 conv/month → Maximize Conversions
├─ 30-50 conversions/month?
│  └─ Use Maximize Conversions
│     └─ When stable CPA → Target CPA
├─ >50 conversions/month?
│  └─ Use Target CPA
│     └─ When revenue tracking → Target ROAS
└─ Revenue tracking active + >50 conv/month?
   └─ Use Target ROAS

Meta Ads Bidding

  • Lowest Cost (default): best for volume, may have CPA variance
  • Cost Cap: sets CPA ceiling, may reduce volume
  • Bid Cap: maximum bid per auction, most control
  • ROAS Goal: target return on ad spend
  • CBO vs ABO: CBO for proven campaigns, ABO for testing

LinkedIn Bidding

  • Cost Per Send (CPS): for Message Ads
  • Manual CPC: recommended starting point for cost control
  • Cost Cap: efficiency at scale with predictable CPA
  • Maximum Delivery: highest volume, most expensive. Use only for scale with established data
  • Target Cost: for predictable CPA

TikTok Bidding

  • Lowest Cost: maximize conversions within budget (volume)
  • Cost Cap: set maximum CPA (efficiency)
  • Bid Cap: maximum bid per impression
  • Budget ≥50x CPA per ad group for learning phase exit

Microsoft Bidding

  • Mirror Google strategy but bid 20-35% lower
  • Manual CPC for low-volume campaigns (Enhanced CPC deprecated on Google March 2025; verify Microsoft availability before recommending)
  • Target CPA / Target ROAS for automated (requires 15+ conversions/30 days)

v1.5 Bidding Innovations

Google AI Max for Search

  • 14% conversion lift in early testing
  • Requires strong negative keyword lists (AI Max casts a wider net)
  • DSA likely consolidated into AI Max by Q2 2026
  • Best for: accounts with mature conversion tracking and keyword history

TikTok Smart+ Modular Control (2025)

  • Lock targeting, creative, budget, or placement independently (mix of manual and AI)
  • ROAS performance: 1.41-1.67x in early adopter data
  • Replaces all-or-nothing automation approach
  • Best for: advertisers wanting partial AI control without full black-box

Apple Ads Maximize Conversions

  • GA: February 26, 2026. AI-powered auto-bidder for Apple Ads
  • Target CPA based on weekly average (not per-conversion)
  • Daily budget must be >=5x target CPA for stable performance
  • Two-week learning phase required; avoid changes during learning
  • Currently supports installs only (not post-install events)

Meta Advantage+ Bidding

  • Automatic optimization across all placements within Advantage+ Sales campaigns
  • Budget automatically shifts to highest-performing placements in real time
  • Best combined with broad targeting and high creative volume

Scaling Assessment

Ready to Scale (Green Light)

  • CPA consistently below target for 2+ weeks
  • ≥50 conversions per week (learning phase exited)
  • CTR stable or improving
  • ROAS above target
  • No creative fatigue signals

20% Rule

Never increase budget by more than 20% at a time:

  • Week 1: $100/day → $120/day
  • Week 2: $120/day → $144/day
  • Week 3: $144/day → $173/day
  • Monitor 3-5 days after each increase for performance stability

Scaling Methods

  1. Vertical: increase budget on winning campaigns (20% rule)
  2. Horizontal: duplicate winning campaigns to new audiences
  3. Platform expansion: add budget on new platforms
  4. Geographic expansion: test new markets/regions
  5. Format expansion: test new ad formats on same platform

Kill List Assessment

3x Kill Rule

  • Any campaign/ad group with CPA >3x target → flag for pause
  • Review spend in last 14 days with no conversions → flag for pause
  • Creative with CTR >50% below platform benchmark → flag for creative kill

Kill Decision Framework

ScenarioData RequiredAction
CPA >3x target≥7 days data, ≥20 clicksPause immediately
No conversions≥$100 spend or ≥50 clicksPause and diagnose
CTR <50% of benchmark≥1,000 impressionsKill creative, test new
ROAS <50% of target≥14 days dataReduce budget 50% or pause

MER (Marketing Efficiency Ratio)

MER = Total Revenue / Total Marketing Spend
  • Assess blended efficiency across all platforms
  • Target MER varies by business: 3x-10x depending on margins
  • Use MER to evaluate overall health, not just per-platform ROAS
  • Incrementality testing recommended for MER accuracy

Output

Budget & Bidding Assessment

Budget Allocation Health

Allocation Strategy:  ████████░░  XX/100
Bidding Strategies:   ██████████  XX/100
Scaling Readiness:    ███████░░░  XX/100
Budget Sufficiency:   █████░░░░░  XX/100

Deliverables

  • BUDGET-STRATEGY-REPORT.md: Full allocation and bidding analysis
  • Current vs recommended budget split (pie chart data)
  • Bidding strategy recommendations per platform/campaign
  • Scale list: campaigns ready for more budget
  • Kill list: campaigns/ad groups to pause immediately
  • MER analysis and trend
  • Quick Wins for immediate budget optimization

平台分布

Codex

35.61%
按下载量换算1,115

Claude

30.69%
按下载量换算961

Cursor

20.65%
按下载量换算647

Gemini CLI

11.01%
按下载量换算345

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。目前只有一个公开来源,建议同时核对源仓库。

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