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Plan global paid growth across Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and DSP/programmatic by comparing country cost, co...

综合技能

作者:danyangliu @danyangliu-sandwichlab

许可证:MIT-0

MIT-0 ·免费使用、修改和重新分发。无需归因。

版本:v1.0.0

统计:⭐ 0 · 176 · 0 current installs · 0 all-time installs

0

安装量(当前) 0

🛡 VirusTotal :良性 · OpenClaw :良性

Package:danyangliu-sandwichlab/global-ads-helper

安全扫描(ClawHub)

  • VirusTotal :良性
  • OpenClaw :良性

OpenClaw 评估

The skill is an instruction-only planner for global paid-media strategy and does not request credentials, install software, or instruct the agent to access unrelated system resources — its declared purpose matches its runtime instructions.

目的

Name/description (global ads planning across major ad platforms) align with the SKILL.md: it provides scoring, allocation, ROI forecasting and rollout guidance. The skill does not request platform API keys or unrelated capabilities, which is coherent for a strategy-only helper.

说明范围

SKILL.md contains purely high-level workflows, decision rules, input/output contracts and examples. It does not instruct the agent to read local files, access environment variables, call external endpoints, or exfiltrate data beyond producing planning outputs.

安装机制

No install spec and no code files — instruction-only skill. Nothing will be written to disk or downloaded, which is low risk and consistent with the described behavior.

证书

The skill requires no environment variables, credentials, or config paths. For a planning/strategy skill this is proportionate; it does not request unrelated secrets or broad access.

持久

always is false and model invocation is allowed (platform default). The skill does not request permanent system presence or attempt to modify other skills or system-wide settings.

综合结论

This skill is internally consistent and low-risk as provided: it only offers planning logic and examples and doesn't request credentials or install code. Before using it in production, consider: (1) if you want the agent to execute live operations (push budgets, query ad accounts), you'll need to provide platform API credentials — validate any future version that adds API calls; (2) review generated recommendations for compliance with country-…

安装(复制给龙虾 AI)

将下方整段复制到龙虾中文库对话中,由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库(龙虾 AI)执行:为本机安装 OpenClaw 技能「Global Ads Helper」。简介:Plan global paid growth across Meta (Facebook/Instagram), Google Ads, TikTok Ad…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装:https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/danyangliu-sandwichlab/global-ads-helper/SKILL.md
(来源:yingzhi8.cn 技能库)

SKILL.md

打开原始 SKILL.md(GitHub raw)

---
name: global-ads-helper
description: Plan global paid growth across Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and DSP/programmatic by comparing country cost, competition intensity, budget synergy, and expansion ROI.
---

# Global Ads Helper

## Purpose
Core mission:
- Analyze market-level traffic cost and competition intensity by country.
- Design cross-channel budget allocation and coordination strategy.
- Forecast expansion ROI across markets.
- Generate global rollout recommendation and risk controls.

## When To Trigger
Use this skill when the user asks for:
- multi-country growth strategy
- global channel budget allocation
- market expansion ROI prediction
- international ads rollout plan

High-signal keywords:
- global ads, market, cost, competition
- allocation, budget, forecast, roi, roas
- scale, strategy, revenue, expansion

## Input Contract
Required:
- target_markets
- expansion_objective
- total_budget
- baseline_market_performance

Optional:
- localization_resources
- compliance_constraints_by_country
- logistics_constraints
- currency_risk_assumptions

## Output Contract
1. Market Attractiveness Matrix
2. Channel Allocation by Market
3. Expansion ROI Forecast
4. Rollout Sequence and Dependencies
5. Market Risk Alert List

## Workflow
1. Rank markets by cost, competition, and conversion potential.
2. Assign channel roles per market maturity.
3. Simulate budget scenarios for each rollout stage.
4. Forecast ROI and payback by region.
5. Output phased expansion plan with risk triggers.

## Decision Rules
- If market CAC is high and data depth is low, start with discovery budget only.
- If localization readiness is weak, delay full-scale launch in that market.
- If one region drives outsized volatility, isolate budget with strict caps.
- If currency risk is elevated, widen ROI confidence intervals.

## Platform Notes
Primary scope:
- Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, DSP/programmatic

Platform behavior guidance:
- Use market-specific channel order; avoid global one-size plans.
- Match creative localization depth to market entry stage.

## Constraints And Guardrails
- Do not compare markets without consistent attribution definitions.
- Keep regional assumptions explicit and revisable.
- Flag legal/policy differences per country before launch.

## Failure Handling And Escalation
- If country-level data is sparse, output exploratory plan with validation milestones.
- If compliance blockers exist, mark blocked markets and reroute budget.
- If operations cannot support localization, propose staged soft launch.

## Code Examples
### Market Scoring Table

    market: DE
    cpc_index: 1.2
    competition_score: 0.74
    conversion_score: 0.63
    priority: medium

### Expansion Allocation (JSON)

    {
      "phase_1": {"US": 0.45, "UK": 0.30, "AU": 0.25},
      "phase_2": {"DE": 0.20, "FR": 0.20, "JP": 0.10}
    }

## Examples
### Example 1: Initial global rollout
Input:
- Launch in 3 English-speaking markets

Output focus:
- market ranking
- channel-by-market plan
- phase-1 risk controls

### Example 2: Add APAC market
Input:
- Existing US/EU campaigns stable
- Wants APAC expansion

Output focus:
- market attractiveness score
- budget impact simulation
- localization requirements

### Example 3: Global budget shock
Input:
- Budget cut by 25% mid-quarter

Output focus:
- market reprioritization
- protection strategy
- revised ROI forecast

## 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