/ads-attribution
Audit cross-platform attribution, conversion definitions, reporting windows, GA4, AdServices and AdAttributionKit, MMPs, browser and server events, offline conversions, and platform reconciliation. Use for attribution audit, attribution models, conversion windows, requests to
$ npx -y skills add AgriciDaniel/claude-ads --skill ads-attribution --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/ads-attribution
Context preview
The summary Claude sees to decide when to auto-load this skill.
Audit cross-platform attribution, conversion definitions, reporting windows, GA4, AdServices and AdAttributionKit, MMPs, browser and server events, offline conversions, and platform reconciliation. Use for attribution audit, attribution models, conversion windows, requests to
SKILL.md
ads-attribution.SKILL.mdname: ads-attribution
description: "Audit cross-platform attribution, conversion definitions, reporting windows, GA4, AdServices and AdAttributionKit, MMPs, browser and server events, offline conversions, and platform reconciliation. Use for attribution audit, attribution models, conversion windows, requests to add or total Meta and Google conversions, incompatible reporting-window aggregation, GA4 attribution, MMP review, AppsFlyer, Adjust, Branch, Singular, or cross-platform discrepancies."
Attribution Audit
1. Read the main `ads` contract and normalized account snapshots. 2. Declare the business conversion, value, data window, timezone, currency, and decision the attribution analysis must support. 3. Inventory every browser, server, platform, analytics, MMP, offline, and app attribution source with its identity, counting, deduplication, and privacy rules. 4. Reconcile comparable events and explain differences caused by eligibility, view-through rules, consent, modeled data, conversion lag, thresholds, or scope. 5. Separate measurement quality from platform-reported performance. 6. Return findings, contradictions, confidence, missing evidence, and a measurement improvement plan through the common JSON contract.
Do not assume one platform is ground truth, add incompatible reports together, or recommend an attribution model without the operator's decision context.
Comparability gate
Reject aggregation until the sources share, or are explicitly normalized to, the same conversion event and value definition, attribution window, click/view scope, counting method, deduplication identity, timezone, currency, attribution model, and modeled-data treatment. Until then, report the values side by side with their definitions; do not compute a total.
Example: Meta seven-day conversions and Google thirty-day conversions are incompatible. Refuse to add them, reconcile windows and definitions first, and only aggregate a newly comparable dataset.
Read more
name: ads-attribution description: "Audit cross-platform attribution, conversion definitions, reporting windows, GA4, AdServices and AdAttributionKit, MMPs, browser and server events, offline conversions, and platform reconciliation. Use for attribution audit, attribution models, conversion windows, requests to add or total Meta and Google conversions, incompatible reporting-window aggregation, GA4 attribution, MMP review, AppsFlyer, Adjust, Branch, Singular, or cross-platform discrepancies."
Attribution Audit
1. Read the main `ads` contract and normalized account snapshots. 2. Declare the business conversion, value, data window, timezone, currency, and decision the attribution analysis must support. 3. Inventory every browser, server, platform, analytics, MMP, offline, and app attribution source with its identity, counting, deduplication, and privacy rules. 4. Reconcile comparable events and explain differences caused by eligibility, view-through rules, consent, modeled data, conversion lag, thresholds, or scope. 5. Separate measurement quality from platform-reported performance. 6. Return findings, contradictions, confidence, missing evidence, and a measurement improvement plan through the common JSON contract.
Do not assume one platform is ground truth, add incompatible reports together, or recommend an attribution model without the operator's decision context.
Comparability gate
Reject aggregation until the sources share, or are explicitly normalized to, the same conversion event and value definition, attribution window, click/view scope, counting method, deduplication identity, timezone, currency, attribution model, and modeled-data treatment. Until then, report the values side by side with their definitions; do not compute a total.
Example: Meta seven-day conversions and Google thirty-day conversions are incompatible. Refuse to add them, reconcile windows and definitions first, and only aggregate a newly comparable dataset.
Claude-first, portable paid-media operations for agencies, consultants, and in-house performance teams. Claude Ads turns authorized exports or account reads into source-grounded audits, plans, creative workflows, experiments, monitoring, and reports.
Repo: AgriciDaniel/claude-ads
Other skills on claude-ads.
- /ads-amazon
Audit Amazon Ads profiles, regions, Sponsored Products, Sponsored Brands, Sponsored Display, DSP, portfolios, targeting, search terms, retail readiness, creative, budgets, ACOS, TACOS, reporting, and policy. Use for Amazon Ads, sponsored ads, Amazon PPC, ACOS, TACOS, ASIN
Open skill - /ads-apple
Audit Apple Ads measurement, AdServices and AdAttributionKit, campaign and keyword structure, Search Match, App Store placements, custom product pages, bidding, budgets, MMP reconciliation, and policy. Use for Apple Ads, Apple Search Ads, App Store ads, Search Match, custom
Open skill - /ads-audit
Run a source-grounded paid-advertising audit for one or more of Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for full ad checks, account health reviews, paid-media diagnostics, partial audits after authentication or
Open skill - /ads-budget
Plan and review paid-media budgets, bidding, pacing, marginal return, forecasts, CPA, ROAS, MER, LTV:CAC, constraints, and allocation across supported platforms. Use for ad budget allocation, media budget, bidding strategy, scaling, spend pacing, budget forecast, ROAS target, or
Open skill - /ads-competitor
Research competitor paid-ad presence, messaging, creative, formats, landing pages, keyword and auction signals, transparent ad libraries, and strategic gaps across supported platforms. Use for competitor ads, ad libraries, ad spy, competitive PPC analysis, competitor creative,
Open skill - /ads-create
Create source-grounded paid-ad campaign concepts, messaging, copy, creative briefs, and production plans from a validated brand profile, campaign objective, platform requirements, and optional audit evidence. Triggers on: campaign brief, campaign concepts, create a campaign, ad
Open skill

