google-ads-rsas

GitHub

基于Google Ads实时数据(MCP或导出)分析搜索词、意图和表现,提取买家语言,生成或优化响应式搜索广告(RSA)的标题和描述草稿。

skills/google-ads-rsas/SKILL.md TheMattBerman/google-ads-copilot

触发场景

需要优化Google Ads RSA广告素材 根据搜索词报告调整广告文案 自动化生成广告创意草稿

安装

npx skills add TheMattBerman/google-ads-copilot --skill google-ads-rsas -g -y
更多选项

不安装直接使用

npx skills use TheMattBerman/google-ads-copilot@google-ads-rsas

指定 Agent (Claude Code)

npx skills add TheMattBerman/google-ads-copilot --skill google-ads-rsas -a claude-code -g -y

安装 repo 全部 skill

npx skills add TheMattBerman/google-ads-copilot --all -g -y

预览 repo 内 skill

npx skills add TheMattBerman/google-ads-copilot --list

SKILL.md

Frontmatter
{
    "name": "google-ads-rsas",
    "description": "Generate or refine Google Ads RSA recommendations using real buyer language from search terms, intent clusters, and winning modifiers. Pulls live data via MCP or works with manual exports. Produces RSA refresh drafts."
}

Google Ads RSAs

Read first:

  • google-ads/references/operator-thesis.md
  • google-ads/references/query-patterns.md
  • google-ads/references/intent-map.md
  • google-ads/references/rsa-playbook.md
  • google-ads/references/deliverable-templates.md

Read workspace if available:

  • workspace/ads/account.md
  • workspace/ads/goals.md
  • workspace/ads/intent-map.md
  • workspace/ads/queries.md
  • workspace/ads/winners.md
  • workspace/ads/assets.md
  • workspace/ads/learnings.md

Data Acquisition

Connected Mode (MCP available)

Pull via the search tool on google-ads-mcp:

Primary: RSA asset performance:

SELECT
  asset.text_asset.text,
  asset.type,
  ad_group_ad_asset_view.performance_label,
  ad_group_ad_asset_view.field_type,
  campaign.name,
  ad_group.name,
  metrics.impressions,
  metrics.clicks,
  metrics.conversions
FROM ad_group_ad_asset_view
WHERE segments.date DURING LAST_30_DAYS
  AND campaign.status = 'ENABLED'
ORDER BY metrics.impressions DESC

Supplementary: Search terms (for buyer language extraction):

SELECT
  search_term_view.search_term,
  campaign.name,
  metrics.conversions,
  metrics.clicks,
  metrics.cost_micros
FROM search_term_view
WHERE segments.date DURING LAST_30_DAYS
  AND metrics.conversions > 0
ORDER BY metrics.conversions DESC
LIMIT 200

Retrieval ladder — if the search-term query returns no rows, follow the shared retrieval ladder in data/search-term-retrieval.md. In pmax-fallback mode, use rows for buyer-language extraction only (language signal, not per-term performance). In limited mode, rely on existing asset performance data for copy direction.

Supplementary: RSA ad-level data:

SELECT
  campaign.name,
  ad_group.name,
  ad_group_ad.ad.responsive_search_ad.headlines,
  ad_group_ad.ad.responsive_search_ad.descriptions,
  ad_group_ad.ad.final_urls,
  metrics.impressions,
  metrics.clicks,
  metrics.conversions
FROM ad_group_ad
WHERE ad_group_ad.ad.type = 'RESPONSIVE_SEARCH_AD'
  AND campaign.status = 'ENABLED'
  AND segments.date DURING LAST_30_DAYS

See data/gaql-recipes.md for additional queries.

Export Mode (no MCP)

Ask the user for:

  • RSA asset report (headlines, descriptions, performance labels)
  • Or RSA preview from the ads tab
  • Search terms report (for buyer language extraction)

Process

  1. Announce mode (connected/export).
  2. Identify the target query cluster or intent bucket.
  3. For search-term buyer language, run the shared retrieval ladder (data/search-term-retrieval.md). In pmax-fallback, use rows for language extraction only. In limited, rely on asset performance data.
  4. Extract buyer language and repeated modifiers from converting search terms when available, or from PMax query rows when only language visibility is available.
  5. Review current RSA assets: what's BEST, GOOD, LOW, UNRATED?
  6. Determine the core promise and LP fit.
  7. Recommend RSA components: headline themes, description angles, message hierarchy.
  8. Save outputs to workspace memory.

Draft Output

RSA Refresh Draft

Trigger: Analysis shows (a) LOW-performing assets that could be replaced, or (b) buyer language patterns not represented in current ads.

Create using drafts/templates/rsa-draft.md:

  • Write to workspace/ads/drafts/YYYY-MM-DD-[account-slug]-rsa-refresh.md
  • Include specific headlines (≤30 chars) and descriptions (≤90 chars)
  • Note pin recommendations (use sparingly)
  • Note which assets to consider removing and why
  • Source each new asset to the buyer language it came from
  • Update workspace/ads/drafts/_index.md

Always update workspace memory:

  • workspace/ads/assets.md — current asset inventory and new recommendations
  • workspace/ads/winners.md — high-performing query language
  • workspace/ads/queries.md — buyer language patterns

Rules

  • Do not write generic ads for mixed intent.
  • Use real query language where possible.
  • Keep LP alignment explicit.
  • If the intent bucket is weak or noisy, say so before generating ads.

版本历史

  • 2c253ee 当前 2026-07-25 07:33

同 Skill 集合

google-ads/SKILL.md
skills/google-ads-apply/SKILL.md
skills/google-ads-audit/SKILL.md
skills/google-ads-budget/SKILL.md
skills/google-ads-connect/SKILL.md
skills/google-ads-daily/SKILL.md
skills/google-ads-draft-summary/SKILL.md
skills/google-ads-intent-map/SKILL.md
skills/google-ads-landing-review/SKILL.md
skills/google-ads-negatives/SKILL.md
skills/google-ads-plan/SKILL.md
skills/google-ads-pmax/SKILL.md
skills/google-ads-search-terms/SKILL.md
skills/google-ads-structure/SKILL.md
skills/google-ads-tracking/SKILL.md

元信息

文件数
0
版本
2c253ee
Hash
a6eea234
收录时间
2026-07-25 07:33

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