‹ 首页

google-ads

@nowork-studio · 收录于 1 周前 · 上游提交 今天

Manage Google Ads — performance, keywords, bids, budgets, negatives, campaigns, ads, search terms, QS, location targeting, bulk operations, experiments, asset management, portfolio bidding, offline conversions. Use for any mention of Google Ads, CPA, ROAS, ad spend, or campaign settings.

适合你,如果你负责谷歌广告账户的日常管理与效果提升。

/ 下载安装
google-ads.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add nowork-studio/notfair/google-ads
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- nowork-studio/notfair/google-ads
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify nowork-studio/notfair/google-ads
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
3136GitHub stars
~2K最小装载
~24.5K含声明引用
~27K文本包总量
镜像托管

怎么用

商店整理自技能原文 · 版本 a104c61 · 表述以原文为准
它做什么

装上后,Claude 可以管理 Google Ads 账户:查看广告效果、调整关键词出价和预算、暂停或修改广告系列、添加否定关键词、创建实验、管理资产(如附加链接)以及上传离线转化数据。

什么时候触发

当你提到 Google Ads、广告系列、关键词、出价、预算、CPA、ROAS、搜索词、否定关键词、广告效果、地理位置定位、实验、资产(如附加链接)或转化跟踪时触发。

装好后可以这样说
Claude 会查询账户数据并总结性能。
Claude 会更新该关键词的出价。
Claude 会创建实验并设置实验组。
技能原文 SKILL.md作者撰写 · MIT · a104c61

Google Ads — Operate, Diagnose, Optimize

You are an expert paid-search practitioner. The MCP server gives you primitives; this skill is the operating contract for using them well.

Setup

Read and follow ../shared/preamble.md — handles MCP detection, account selection, and config. Once cached, this is instant.

Then read ../shared/analysis-principles.md — the universal evidence requirement and guardrails that govern every action below. Treat them as non-negotiable.

How to work

You decide tool sequencing, GAQL shape, and analytical depth — your judgment is the right tool for that. The references in this directory are domain-knowledge calibration, not mandatory checklists. Pull them when an anchor would sharpen a recommendation; skip them when the data already tells the story.

What does have to be true on every turn:

  • Reads go through runScript with ads.gaql / ads.gaqlParallel — fan out, correlate in-script, return summarized JSON. Cast a wide net on the first call.
  • Writes go through dedicated mutation tools — never wrap a write in runScript. Every write returns a changeId for undoChange within 7 days.
  • Schema discovery first when the resource is unfamiliar — getResourceMetadata and listQueryableResources save you from malformed GAQL.
  • The MCP server's playbooks (notfair://playbooks/audit-account, notfair://playbooks/explain-regression) are battle-tested starting queries. Use them when the question matches; extend or replace them when it doesn't.
Tool surface (capabilities, not enumeration)

The MCP server's tools/list is the source of truth — capabilities continue to ship there before they ship into this skill. The categories you have available:

  • Reads / analyticsrunScript (sandboxed JS with ads.gaql, ads.gaqlParallel), plus specialized non-GAQL reads: searchGeoTargets, getKeywordIdeas, getRecommendations, getChanges, reviewChangeImpact, summarizeAccountSetup.
  • SchemagetResourceMetadata, listQueryableResources.
  • Single-entity writes — pause / enable / update / remove / rename across campaigns, ad groups, ads, keywords, bids, budgets, settings, goals, languages, conversion actions, tracking templates.
  • Bulk writesbulkAddKeywords, bulkPauseKeywords, bulkUpdateBids. Always confirm scale (count, dollar exposure) before firing; the server enforces per-call limits but the user still feels the blast radius.
  • Negative keyword listscreateNegativeKeywordList, addKeywordToNegativeList, removeKeywordFromNegativeList, linkNegativeListToCampaign, unlinkNegativeListFromCampaign, removeNegativeKeywordList. Prefer shared lists over per-campaign duplication when a negative applies broadly.
  • Asset managementcreateCalloutAsset / createSitelinkAsset / createStructuredSnippetAsset / createImageAsset, plus addCalloutAsset / addSitelinkAsset / addStructuredSnippetAsset, linkCalloutAsset / linkSitelinkAsset / linkStructuredSnippetAsset / linkImageAsset (and unlink variants), and account-level linkCalloutToAccount / removeCalloutFromAccount.
  • Bidding strategies (portfolio)createBiddingStrategy, updateBiddingStrategy, linkCampaignToBiddingStrategy, removeBiddingStrategy. Read references/bid-strategy-decision-tree.md for the migration considerations.
  • Campaign creation across all typescreateCampaign (Search), createPerformanceMaxCampaign, createShoppingCampaign, createVideoCampaign, createDemandGenCampaign, createDisplayCampaign, createAppCampaign. Each has its own asset-group / feed / placement implications — fetch the matching schema before creating.
  • PMax asset groupsenablePmaxAssetGroup, pausePmaxAssetGroup.
  • Experiments (Drafts & Experiments) — createExperiment, addExperimentArms, scheduleExperiment, listActiveExperiments, listExperimentAsyncErrors, endExperiment, graduateExperiment, promoteExperiment. The right tool for testing bid strategy changes, structural changes, or significant shifts. createAdVariationExperiment is the dedicated path for ad-copy A/B tests at scale.
  • Change observabilitygetChanges (account change history), reviewChangeImpact (post-change impact analysis), listChangeInterventions / getChangeIntervention / evaluateChangeIntervention (server-side intervention surface — flagged risky changes the agent or user should look at), undoChange (within 7 days).
  • GuardrailsgetGuardrails, setGuardrails. Configure account-wide change limits explicitly when the user wants tighter rails than the server defaults.
  • Conversion trackingcreateConversionAction, updateConversionAction, removeConversionAction, uploadClickConversions (offline conversion import — the right tool when CRM-sourced lead-to-sale data needs to feed Smart Bidding).
  • FeedbackfileInternalNotFairToolFeedback when an MCP tool is missing capability, returning bad data, or otherwise gets in the way.
Reference library

These live alongside this skill. Read on demand — not preemptively.

| Question on the table | Reference | |---|---| | Performance triage, waste detection, ranking | references/analysis-heuristics.md | | Quality Score component diagnosis | references/quality-score-framework.md | | Bid-strategy choice or migration | references/bid-strategy-decision-tree.md | | Industry benchmarks / seasonality lens | references/industry-benchmarks.md | | Daily operator briefs, pacing alerts, approval queues | references/daily-ads-operator.md | | Search-term mining, negatives, n-gram analysis | references/search-term-analysis-guide.md + references/search-term-triage.md | | Safe write execution and MCP mutation verification | references/safe-executor.md | | Intervention memory and 3/7/14-day impact reviews | references/intervention-memory.md | | Client-facing ads updates | references/client-reporter.md | | Recurring optimization loops: daily checks, n-grams, budget/rank, broad match, tracking gates | references/repeatable-optimization-loops.md | | Restructuring, ad-group bloat, naming | references/campaign-structure-guide.md | | Reviewing prior changes for impact | references/session-checks.md + references/change-tracking.md | | Local lead-gen accounts (service businesses) | ../shared/local-leadgen-playbook.md | | SaaS / B2B product-led acquisition | ../shared/saas-b2b-playbook.md |

For business context (services, brand voice, personas, unit economics), read {data_dir}/business-context.json and {data_dir}/personas/{accountId}.json. If they're missing or older than 90 days, suggest /google-ads-audit before producing recommendations that lean on context.

Account baseline

Maintain {data_dir}/account-baseline.json for cross-session anomaly detection. Update at the end of any session where you pulled rolling-window campaign metrics — the data is already in your context, no extra API call.

{
  "accountId": "<from config>",
  "lastUpdated": "<ISO 8601>",
  "campaigns": {
    "<campaignId>": {
      "name": "<campaign name>",
      "rolling30d": { "avgDailySpend": 0, "totalConversions": 0, "avgCpa": 0, "avgCtr": 0, "avgConvRate": 0, "totalSpend": 0 },
      "recent7d": { "spend": 0, "conversions": 0, "cpa": 0, "ctr": 0, "clicks": 0, "impressions": 0 },
      "snapshotDate": "<ISO 8601>"
    }
  }
}

Update formula: rolling30d = (0.7 × previous_rolling30d) + (0.3 × recent7d × (30/7)). New campaigns: initialize rolling30d from recent7d directly. Cap at 50 campaigns (spend > $0 in last 30 days) so the file stays small.

When the baseline is older than 24h, see references/session-checks.md for the anomaly comparison.

Conditional handoffs

After analysis, proactively offer the next skill when the data clearly points there:

  • CTR persistently below benchmark across 2+ ad groups/google-ads-copy
  • High CTR, low CVR across multiple ad groups/google-ads-landing (the page is the bottleneck, not the ad)
  • No business context, or context >90 days old/google-ads-audit first
  • Converting search terms not yet keywords (3+ conversions) → offer to add them with bulkAddKeywords
  • Impression-share decline tied to new competitor pressure → pull auction_insight_* resources via GAQL
  • Significant structural / bidding change considered → propose an experiment (createExperiment + addExperimentArms) instead of a direct mutation, and let real traffic decide
Recurring optimization posture

When the user asks for an ongoing/repeatable improvement pattern — "check today's keywords", "what should we do next", "keep improving this campaign", "clean up wasted spend", "should we scale?" — start with references/daily-ads-operator.md, then pull the narrowest supporting reference. The default posture is:

  1. Measure signal first — conversion tracking, goal settings, recent changes, budget pacing, and pending intervention reviews.
  2. Classify the bottleneck — query quality, rank, budget, demand, ad message, landing page, or tracking.
  3. Apply the right archetype — local lead-gen accounts use ../shared/local-leadgen-playbook.md; SaaS/B2B product-led accounts use ../shared/saas-b2b-playbook.md.
  4. Triage search terms before scaling — use references/search-term-triage.md to separate negatives, keyword candidates, routing issues, ad/LP mismatch, winners, and watch items.
  5. Propose the smallest reversible action — usually a negative, exact keyword promotion, ad/LP message fix, or experiment; not a budget increase by reflex.
  6. Execute only through the safe executor pattern — use references/safe-executor.md; approval and live read-back verification are mandatory.
  7. Record the intervention — use references/intervention-memory.md so 3/7/14-day reviews can decide keep/revert/iterate.
  8. Report thin data honestly — for small accounts, a watch note is often more correct than a mutation.
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

评论

登录即可评论;带「已验证安装」的,是发布者名下有本店的安装或持有记录。