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.
git 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/competitive-auction-insights)<a href="https://agentmods.dev/commands/ad-superpowers/ad-superpowers-plugin/competitive-auction-insights"><img src="https://agentmods.dev/badge/commands/ad-superpowers/ad-superpowers-plugin/competitive-auction-insights/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/commands/ad-superpowers/ad-superpowers-plugin/competitive-auction-insights"><img src="https://agentmods.dev/badge/commands/ad-superpowers/ad-superpowers-plugin/competitive-auction-insights.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 | $0.00027 | $0.01106 |
| Opus 5 | $0.00014 | $0.00553 |
| Sonnet 5 | $0.00005 | $0.00221 |
| Haiku 4.5 | $0.00003 | $0.00111 |
Grade A, and why
competitive-auction-insights 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 9d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Platforms: google_ads 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.
Competitive Auction Insights
Analyze the competitive landscape in Google Ads using auction insights data.
- Focus: all campaigns
OUTPUT FORMAT (CRITICAL - follow this EXACT structure)
Competitive Position
| Metric | Your Score | Benchmark | Status |
|---|---|---|---|
| Search Impression Share | XX% | 30-40% (non-brand) / 80%+ (brand) | Good/Poor |
| Top of Page Rate | XX% | 40-60% | Good/Poor |
| Absolute Top Rate | XX% | 15-25% | Good/Poor |
| Avg Outranking Share | XX% | - | - |
Top Competitors (by overlap rate)
| Competitor | Overlap | Pos Above Rate | Outranking Share | Threat |
|---|---|---|---|---|
| domain.com | XX% | XX% | XX% | HIGH/MED/LOW |
Threat level: HIGH = overlap >60% AND position above >50%. MED = overlap >40%. LOW = all others.
Competitive Strength Score
Score = (Impression Share * 0.3) + (Top of Page Rate * 0.3) + (Avg Outranking Share * 0.4)
90-100: Dominant | 70-89: Strong | 50-69: Competitive | <50: Weak
Recommendations
Defensive (protect your position):
- [Brand protection actions]
- [Position defense actions]
Offensive (gain ground):
- [Competitor weakness to exploit]
- [Market gap identified]
Budget Implication: To gain 10% more impression share: +EUR X,XXX/month estimate.
EXECUTION STEPS
Step 1: List accounts
google_ads_list_accounts()
Identify the target account. If user specified an account, use it directly.
Step 2: Pull auction insights for search campaigns
google_ads_run_gaql(
customer_id="CUSTOMER_ID",
query="SELECT campaign.name, campaign.campaign_budget, metrics.search_impression_share, metrics.search_top_impression_share, metrics.search_absolute_top_impression_share, metrics.search_budget_lost_impression_share, metrics.search_rank_lost_impression_share FROM campaign WHERE campaign.advertising_channel_type = 'SEARCH' AND campaign.status = 'ENABLED' AND segments.date DURING LAST_30_DAYS ORDER BY metrics.impressions DESC LIMIT 20"
)
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.
- 9d ago First seen · 106 lines · 27 tokens per session scan A ce80c358d548
competitive-auction-insights is a command published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 11d ago), licensed MIT. It adds 27 tokens to every session and 1,106 once invoked, about $0.0001 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
meta-audit
Full Meta Ads account audit, tailored to ecommerce or lead-gen automatically.
setup
First-run setup for the ga-mcp-full MCP server — install the CLI if needed, then complete the browser login.
audit
Google Ads command — audit.
logout
Google Ads command — logout.
status
Google Ads command — status.
checklist
Generate a custom checklist for the current feature based on user requirements.