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ads-execution-hub广告执行中心

Agent Skill

ads-execution-hub 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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

8,491

周安装

361

GitHub Stars

公开资料未说明

下载量

2,975
OpenClaw

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

2

许可证

MIT-0

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:ads-execution-hub(广告执行中心)
来源仓库:https://github.com/danyangliu-sandwichlab/ads-execution-hub
安装命令:
openclaw skills install ads-execution-hub
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install ads-execution-hub

简介

ads-execution-hub 用于跨渠道广告管理,适合在 OpenClaw 中优化多平台投放。

  • 它支持 Meta、Google、TikTok 等平台的活动管理和性能分析。
  • 通过 clawhub 安装后,可结合来源仓库和 README 继续核验集成方式。
  • 安装前需确认权限范围、维护状态及是否触发外部 API 调用。
  • 建议参考原始文档了解配置步骤和权限要求。

SKILL.md

name
ads-execution-hub
description
Ads Execution Hub control skill for ad campaign management and optimization across Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads, and DSP/programmatic.

Ads Execution Hub

Purpose

Core mission:

  • Serve as the dedicated ad operations and optimization interface.
  • Manage planning, launch, monitoring, and scaling across ad channels.
  • Standardize decision policies for bidding, budget, and performance recovery.
  • Output clear operator actions for media teams.

When To Trigger

Use this skill when the user asks for:

  • campaign setup, optimization, or scaling in one or more channels
  • budget and bidding decision support with performance constraints
  • anomaly diagnosis and recovery actions for live campaigns
  • cross-channel media operation playbooks

High-signal keywords:

  • ads execution hub, run ads, campaign, media buyer
  • bidding, budget, allocation, optimize, scale
  • cpa, roas, performance, monitor, abtest

Input Contract

Required:

  • campaign_objective
  • channel_scope
  • budget_constraints
  • recent_performance_snapshot

Optional:

  • creative_state
  • audience_state
  • tracking_health
  • policy_or_account_flags

Output Contract

  1. Campaign Action Plan
  2. Bidding and Budget Policy
  3. AB Test and Scale Model
  4. Monitoring and Alert Plan
  5. Operator Handoff Checklist

Workflow

  1. Normalize objective and KPI constraints.
  2. Evaluate channel readiness and structure quality.
  3. Produce bid and allocation actions.
  4. Attach testing and scaling rules.
  5. Return monitoring triggers and operator checklist.

Decision Rules

  • If measurement confidence is low, limit scale and improve tracking first.
  • If ROAS is stable above threshold, allow staged budget increases.
  • If CPA is unstable, reduce concurrency of experiments.
  • If anomaly risk is high, prefer containment actions first.

Platform Notes

Primary scope:

  • Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads, DSP/programmatic

Platform behavior guidance:

  • Keep channel recommendations execution-specific and auditable.
  • Align bid logic with each platform's optimization mechanics.

Constraints And Guardrails

  • No irreversible changes without rollback conditions.
  • Keep every recommendation tied to KPI impact.
  • Respect policy and account health constraints.

Failure Handling And Escalation

  • If required platform data is missing, return minimum data request list.
  • If policy or account block appears, route to compliance/account helper.
  • If spend risk is severe, trigger emergency control mode.

Code Examples

Campaign Control Spec

objective: improve_roas channels: [Meta, GoogleAds, TikTokAds] budget_mode: staged_scale cpa_ceiling: 42 roas_floor: 2.5

Alert Trigger Rule

if roas_drop_pct > 20 and spend_up_pct > 25: severity: high action: cap_budget_and_notify

Examples

Example 1: Launch and stabilize

Input:

  • New campaign across Meta and TikTok Ads

Output focus:

  • launch checklist
  • first-week controls
  • fallback rules

Example 2: Scale after validation

Input:

  • Stable ROAS for 10 days

Output focus:

  • scale ladder
  • bid policy updates
  • monitoring checkpoints

Example 3: Cross-channel anomaly

Input:

  • Spend surge, mixed conversion signals

Output focus:

  • anomaly triage
  • containment actions
  • next validation steps

Quality Checklist

  • [ ] Required sections are complete and non-empty
  • [ ] Trigger keywords include at least 3 registry terms
  • [ ] Input and output contracts are operationally testable
  • [ ] Workflow and decision rules are capability-specific
  • [ ] Platform references are explicit and concrete
  • [ ] At least 3 practical examples are included

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

96.25%
按下载量换算2,863

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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