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majiayu000/claude-skill-registry

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.

What is claude-skill-registry?

claude-skill-registry is a Claude Code agent skill that 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.

Works with✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/majiayu000/claude-skill-registry/tree/HEAD/skills/other/manage

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Open a new chat with this agent skill pre-loaded.

Documentation

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 / analytics — runScript (sandboxed JS with ads.gaql, ads.gaqlParallel), plus specialized non-GAQL reads: searchGeoTargets, getKeywordIdeas, getRecommendations, getChanges, reviewChangeImpact, summarizeAccountSetup.
  • Schema — getResourceMetadata, 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 writes — bulkAddKeywords, 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 lists — createNegativeKeywordList, addKeywordToNegativeList, removeKeywordFromNegativeList, linkNegativeListToCampaign, unlinkNegativeListFromCampaign, removeNegativeKeywordList. Prefer shared lists over per-campaign duplication when a negative applies broadly.
  • Asset management — createCalloutAsset / 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 types — createCampaign (Search), createPerformanceMaxCampaign, createShoppingCampaign, createVideoCampaign, createDemandGenCampaign, createDisplayCampaign, createAppCampaign. Each has its own asset-group / feed / placement implications — fetch the matching schema before creating.
  • PMax asset groups — enablePmaxAssetGroup, 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 observability — getChanges (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).
  • Guardrails — getGuardrails, setGuardrails. Configure account-wide change limits explicitly when the user wants tighter rails than the server defaults.
  • Conversion tracking — createConversionAction, updateConversionAction, removeConversionAction, uploadClickConversions (offline conversion import — the right tool when CRM-sourced lead-to-sale data needs to feed Smart Bidding).
  • Feedback — fileInternalNotFairToolFeedback 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 tableReference
Performance triage, waste detection, rankingreferences/analysis-heuristics.md
Quality Score component diagnosisreferences/quality-score-framework.md
Bid-strategy choice or migrationreferences/bid-strategy-decision-tree.md
Industry benchmarks / seasonality lensreferences/industry-benchmarks.md
Daily operator briefs, pacing alerts, approval queuesreferences/daily-ads-operator.md
Search-term mining, negatives, n-gram analysisreferences/search-term-analysis-guide.md + references/search-term-triage.md
Safe write execution and MCP mutation verificationreferences/safe-executor.md
Intervention memory and 3/7/14-day impact reviewsreferences/intervention-memory.md
Client-facing ads updatesreferences/client-reporter.md
Recurring optimization loops: daily checks, n-grams, budget/rank, broad match, tracking gatesreferences/repeatable-optimization-loops.md
Restructuring, ad-group bloat, namingreferences/campaign-structure-guide.md
Reviewing prior changes for impactreferences/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.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

majiayu000/claude-skill-registry

Builds, edit or validate Agent Skill through conversational discovery. Use when the user requests to "Create an Agent", "Optimize an Agent" or "Edit an Agent".

majiayu000/claude-skill-registry

Edit existing BMAD agents while maintaining compliance

majiayu000/claude-skill-registry

Edit existing BMAD agents while maintaining compliance

majiayu000/claude-skill-registry

Edit existing BMAD modules while maintaining coherence

majiayu000/claude-skill-registry

Edit existing BMAD modules while maintaining coherence

majiayu000/claude-skill-registry

Analyzes current state and user query to answer BMad questions or recommend the next workflow or agent. Use when user says what should I do next, what do I do now, or asks a question about BMad

majiayu000/claude-skill-registry

Build AI agents with Google ADK Python (Agent Development Kit). Use for multi-agent systems, workflow agents (sequential/parallel/loop), Vertex AI deployment, tool integration, human-in-the-loop.

majiayu000/claude-skill-registry

Build AI agents with Google ADK Python (Agent Development Kit). Use for multi-agent systems, workflow agents (sequential/parallel/loop), Vertex AI deployment, tool integration, human-in-the-loop.

majiayu000/claude-skill-registry

Portfolio allocation and rebalancing optimizer. Manages asset allocation across stocks/cash/bonds, performs periodic rebalancing, and ensures diversification according to market regime and risk tolerance.

majiayu000/claude-skill-registry

Create a hilarious and ultra-realistic video of an anthropomorphic animal acting like a human vlogger in a real-world setting.

majiayu000/claude-skill-registry

Speech-to-text transcription and translation via OpenAI Audio API -- models, response formats, timestamps, prompting, streaming, chunking, and diarization

majiayu000/claude-skill-registry

BlockRun works with Claude Code and Google Antigravity.

majiayu000/claude-skill-registry

This skill should be used when the user asks about libraries, frameworks, API references, or needs code examples. Activates for setup questions, code generation involving libraries, or mentions of specific frameworks like React, Vue, Next.js, Prisma, Supabase, etc.

majiayu000/claude-skill-registry

小省导购员数字人带货版即梦视频提示词生成系统,基于四大智能体协同(提示词生成师、质量管控师、知识库运维师、跨环节适配师),按照"主体+运动+场景+(镜头语言+光影+氛围)"公式输出中英文双版提示词,适配5s短视频。确保人物一致性、视觉连贯性、情绪连贯性,支持知识库智能复用和跨工具适配(Suno音乐、AI绘画),为数字人带货视频提供高质量提示词生成服务。

majiayu000/claude-skill-registry

Upload and manage files using Google Gemini File API via scripts/. Use for uploading images, audio, video, PDFs, and other files for use with Gemini models. Supports file upload, status checking, and file management. Triggers on "upload file", "file API", "upload image", "upload PDF", "upload video", "file management".

majiayu000/claude-skill-registry

CRITICAL: Use for MolyKit AI chat toolkit. Triggers on: BotClient, OpenAI, SSE streaming, AI chat, molykit, PlatformSend, spawn(), ThreadToken, cross-platform async, Chat widget, Messages, PromptInput, Avatar, LLM

majiayu000/claude-skill-registry

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

majiayu000/claude-skill-registry

Analyze images/audio/video with Gemini API (better vision than Claude). Generate images (Imagen 4), videos (Veo 3). Use for vision analysis, transcription, OCR, design extraction, multimodal AI.

majiayu000/claude-skill-registry

Analyze images/audio/video with Gemini API (better vision than Claude). Generate images (Imagen 4), videos (Veo 3). Use for vision analysis, transcription, OCR, design extraction, multimodal AI.

majiayu000/claude-skill-registry

Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory.

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