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 agentmods add commands/ad-superpowers/ad-superpowers-plugin/cross-platform-comparisongit 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/commands/ad-superpowers/ad-superpowers-plugin/cross-platform-comparison)<a href="https://agentmods.dev/commands/ad-superpowers/ad-superpowers-plugin/cross-platform-comparison"><img src="https://agentmods.dev/badge/commands/ad-superpowers/ad-superpowers-plugin/cross-platform-comparison.svg" alt="Measured on agentmods" 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 | $0.00094 | $0.01549 |
| Opus 5 | $0.00047 | $0.00775 |
| Sonnet 5 | $0.00019 | $0.00310 |
| Haiku 4.5 | $0.00009 | $0.00155 |
Grade A, and why
cross-platform-comparison 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 4d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Platforms: meta, google_ads, linkedin, tiktok Tier: pro
This command requires the Ad Superpowers MCP connector to access your ad account data. Connect at https://app.adsuperpowers.ai if you haven't already.
Cross-Platform Performance Comparison
Compare performance across all connected ad platforms for last 30 days, rank by ROAS, and recommend budget reallocations.
OUTPUT FORMAT (CRITICAL - follow this EXACT structure)
PLATFORM OVERVIEW
| Platform | Spend | % Budget | Convs | CPA | ROAS | Rank |
|---|
ATTRIBUTION RECONCILIATION
| Platform | Platform Convs | GA4 Convs | Variance | Status |
|---|---|---|---|---|
| (Normal: Meta <30%, Google <25%, TikTok <40%, LinkedIn <35%) |
WHICH NUMBER TO TRUST
| Use Case | Source | Why |
|---|---|---|
| Single platform optimization | Platform data | Algorithm optimizes on its own signals |
| Cross-channel budget moves | GA4 (adjust +25-35%) | Consistent attribution model |
| Stakeholder reporting | GA4 | Consistency builds trust |
BUDGET REALLOCATION
| Platform | Current | Recommended | Change | Confidence |
|---|---|---|---|---|
| Confidence: HIGH (1000+ convs, >25% diff) | MEDIUM (100-999 convs) | LOW (<100 convs) |
NEXT STEPS
- [Highest confidence reallocation]
- [Second priority]
- [Validation recommendation]
EXECUTION STEPS
Step 1: Discover Accounts
meta_list_ad_accounts()google_ads_list_accounts()linkedin_list_ad_accounts()tiktok_get_advertiser_info()ga4_list_properties()
Step 2: Gather Data
Meta: meta_get_insights(account_id="FROM_STEP_1", date_preset="last_30d", level="account", fields=["spend","impressions","reach","frequency","clicks","actions","action_values","cpm","cpc","ctr","purchase_roas"])
Google Ads: google_ads_run_gaql(customer_id="FROM_STEP_1", query="SELECT campaign.name, metrics.impressions, metrics.clicks, metrics.ctr, metrics.average_cpc, metrics.cost_micros, metrics.conversions, metrics.conversions_value FROM campaign WHERE segments.date DURING LAST_30_DAYS ORDER BY metrics.cost_micros DESC")
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.
- 4d ago First seen · 112 lines · 94 tokens per session scan A cbeb63fdbbf3
cross-platform-comparison is a command published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 6d ago), licensed MIT. It adds 94 tokens to every session and 1,549 once invoked, about $0.0005 per session on Opus 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 2026-08-31.
Other commands, from other repositories
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meta-audit
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ad-brief
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ad-polish
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audit
Google Ads command — audit.