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/weekly-performance-pulsegit 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/weekly-performance-pulse)<a href="https://agentmods.dev/commands/ad-superpowers/ad-superpowers-plugin/weekly-performance-pulse"><img src="https://agentmods.dev/badge/commands/ad-superpowers/ad-superpowers-plugin/weekly-performance-pulse.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 | $0.00013 | $0.00714 |
| Opus 5 | $0.00006 | $0.00357 |
| Sonnet 5 | $0.00003 | $0.00143 |
| Haiku 4.5 | $0.00001 | $0.00071 |
Grade A, and why
weekly-performance-pulse 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Platforms: meta, google_ads Tier: free
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.
Weekly Performance Pulse
Create a weekly performance summary for one connected account per platform using only observed Meta Ads and Google Ads data.
EXECUTION STEPS
This workflow supplies a client-directed plan; it does not provide a server-side runtime executor. Run exactly these four calls in order for the baseline run. Select at most one account per platform, and do not paginate or retry a call in the baseline run.
Step 1: Discover one account per platform
meta_list_ad_accounts()
google_ads_list_accounts()
Choose at most one available account for Meta and one available customer for Google Ads. If a source has no available account or its discovery call fails, record that source as unavailable and continue with the other source.
Step 2: Gather the 14 daily observations
Meta Ads
meta_get_insights(
account_id="FROM_STEP_1",
date_preset="last_14d",
time_increment="1",
level="account",
fields=["spend", "impressions", "clicks", "actions", "action_values", "cpm", "cpc", "ctr", "purchase_roas"]
)
Google Ads
google_ads_run_gaql(
customer_id="FROM_STEP_1",
query="SELECT segments.date, metrics.cost_micros, metrics.impressions, metrics.clicks, metrics.conversions, metrics.conversions_value FROM customer WHERE segments.date DURING LAST_14_DAYS ORDER BY segments.date DESC"
)
OUTPUT FORMAT
TL;DR
Give a concise, evidence-based summary of the available sources. Do not invent metrics, values, currencies, conversions, or causes.
Platform views
For each available platform, report only returned metrics and identify the selected account. Keep Meta actions and Google Ads conversions in separate platform views; do not aggregate conversion types across platforms. Do not aggregate monetary values across currencies.
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 · 76 lines · 13 tokens per session scan A 00121b811b26
weekly-performance-pulse is a command published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 6d ago), licensed MIT. It adds 13 tokens to every session and 714 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
feed-audit
Audit Merchant Center feed quality — disapprovals, attributes, identifiers, custom labels.
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.
ad-brief
Generate a production-ready creative brief from a scripted Pipeline ad. Includes shot list, filming card, B-roll suggestions, text overlay specs, and equipment notes. Ready to print and film.
ad-polish
Strip AI patterns from ad copy and scripts. Makes text sound like a real person wrote it, not a language model. Run on any Pipeline record before launch.
audit
Google Ads command — audit.