Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Ad-Superpowers/ad-superpowers-plugin --skill google-ads-attribution-model-advisorgit clone --depth 1 https://github.com/Ad-Superpowers/ad-superpowers-pluginWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/google-ads-attribution-model-advisor)<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/google-ads-attribution-model-advisor"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/google-ads-attribution-model-advisor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/google-ads-attribution-model-advisor"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/google-ads-attribution-model-advisor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00099 | $0.03640 |
| Opus 5.5 | $0.00040 | $0.01456 |
| Sonnet 5.5 | $0.00020 | $0.00728 |
| Haiku 4.5 | $0.00010 | $0.00364 |
Grade A, and why
google-ads-attribution-model-advisor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 450 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Attribution Model Advisor
Complete guide for choosing, implementing, and evaluating Google Ads attribution models with focus on Data-Driven Attribution (DDA) and cross-channel measurement.
2026 Measurement Foundation: Consent Mode v2 + Enhanced Conversions
Attribution accuracy depends entirely on your measurement stack being compliant and complete. Check this first:
MEASUREMENT HEALTH CHECKLIST (2026)
════════════════════════════════════
1. CONSENT MODE V2 (Required for EEA since March 2024)
├── ad_storage + analytics_storage consent signals firing
├── ad_user_data + ad_personalization signals set
├── Google Tag Manager: Consent Initialization trigger configured
└── Verify: gtag('consent', 'default', {...}) fires BEFORE any ad tags
2. ENHANCED CONVERSIONS (Name unchanged — still "Enhanced Conversions")
├── Hashes first-party user data (email, phone, address)
├── Recovers conversions lost to cookie rejection
├── Setup: Google Ads → Tools → Conversions → Enhanced Conversions
└── Requires privacy policy update
3. ATTRIBUTION MODEL ORDER OF PREFERENCE (2026):
Data-Driven (DDA) > Linear > Position-Based > Time Decay > Last Click
├── First Click: Only for pure awareness measurement
└── Last Click: Legacy only — avoid for Smart Bidding campaigns
Pull Conversion Action Settings via MCP
google_ads_run_gaql(query="
SELECT conversion_action.name,
conversion_action.attribution_model_settings.attribution_model,
conversion_action.counting_type,
conversion_action.include_in_conversions_metric,
conversion_action.click_through_lookback_window_days,
conversion_action.view_through_lookback_window_days,
metrics.conversions, metrics.conversions_value
FROM conversion_action
WHERE conversion_action.status = 'ENABLED'
")
Use this to audit whether DDA is active and whether lookback windows match your sales cycle.
See decision-trees.md for details.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 450 lines · 99 tokens per session scan A 0ad4d949218b
google-ads-attribution-model-advisor is a skill published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 29d ago), licensed MIT. It adds 99 tokens to every session and 3,640 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-11.
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