campaign-battle-report

campaign-battle-report is a command for Claude Code from Ad-Superpowers/ad-superpowers-plugin. It costs 28 tokens per session (969 once invoked), scanned A, original, MIT.

A side-by-side report for comparing two advertising campaigns, time periods, or campaign types. An A/B test compares two versions to see which performs better.

In plain words
What is it for?
Use it to compare campaigns or periods across Meta, Google Ads, LinkedIn, and TikTok using metrics such as clicks, conversions, CPA, and return on ad spend.
Why use it?
It puts spending, results, efficiency, and statistical confidence in one comparison, so small differences are not mistaken for reliable wins.

Command for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Part of the ad-superpowers plugin — 17 skills, 35 commands, 5 agents, 1 MCP server shipped together

Good fit Use it to compare campaigns or periods across Meta, Google Ads, LinkedIn, and TikTok using metrics such as clicks, conversions, CPA, and return on ad spend.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/ad-superpowers/ad-superpowers-plugin/campaign-battle-report
Install

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.

Clone the repo
git clone --depth 1 https://github.com/Ad-Superpowers/ad-superpowers-plugin

Made for: Claude Code.

Or install ad-superpowers, the plugin that ships this one along with the rest of its 17 skills, 35 commands, 5 agents, 1 MCP server.

Wrote 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.

agentmods badge for campaign-battle-report

README.md
[![agentmods](https://agentmods.dev/badge/commands/ad-superpowers/ad-superpowers-plugin/campaign-battle-report/github.svg)](https://agentmods.dev/commands/ad-superpowers/ad-superpowers-plugin/campaign-battle-report)
Your own site
<a href="https://agentmods.dev/commands/ad-superpowers/ad-superpowers-plugin/campaign-battle-report"><img src="https://agentmods.dev/badge/commands/ad-superpowers/ad-superpowers-plugin/campaign-battle-report/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.

agentmods 80×15 button for campaign-battle-report

Your own site · 80×15
<a href="https://agentmods.dev/commands/ad-superpowers/ad-superpowers-plugin/campaign-battle-report"><img src="https://agentmods.dev/badge/commands/ad-superpowers/ad-superpowers-plugin/campaign-battle-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 969 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00028 $0.00969
Opus 5 $0.00014 $0.00485
Sonnet 5 $0.00006 $0.00194
Haiku 4.5 $0.00003 $0.00097

Measured 8d ago against content hash 165bf3505507, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

campaign-battle-report 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 8d 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.

plugin/commands/campaign-battle-report.md · 98 lines

How it starts

The opening of the file, as written. The whole thing — 98 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.

Campaign Battle Report

Compare two campaigns or time periods side-by-side.

Comparison Type: ab_test

OUTPUT FORMAT (CRITICAL - follow this EXACT structure)

CONTESTANTS

  • A: [Campaign/Period A Name]
  • B: [Campaign/Period B Name]
  • Period: [Date Range]

HEAD-TO-HEAD

Metric A B Difference Winner
Spend [amount] [amount] +/-XX% A/B
Impressions [value] [value] +/-XX% A/B
Clicks [value] [value] +/-XX% A/B
CTR X.XX% X.XX% +/-XX% A/B
Conversions [value] [value] +/-XX% A/B
Conv. Rate X.XX% X.XX% +/-XX% A/B
CPA [amount] [amount] +/-XX% A/B
ROAS X.XXx X.XXx +/-XX% A/B

WINNER DECLARATION

WINNER: [A or B]

  • Primary KPI ([metric]): [Winner] outperformed by XX%
  • Statistical Significance: [Significant / Not Significant / Need More Data]
  • Confidence Level: [High / Medium / Low]

KEY INSIGHTS

  1. [Main takeaway]
  2. [Secondary insight]
  3. [Unexpected finding]

RECOMMENDED ACTIONS

  1. [Action based on results]
  2. [Action based on results]

CAVEATS

  • [Data quality issues, external factors, sample size notes]

EXECUTION STEPS

Step 1: Identify Campaigns to Compare

Ask user for campaign names/IDs and platform, or time periods.

Step 2: Pull Campaign Data

Meta (A/B test): meta_get_insights(account_id="...", level="campaign", filtering=[{"field":"campaign.name","operator":"CONTAIN","value":"CAMPAIGN_A"}], date_preset="last_30d", fields=["spend","impressions","clicks","actions","action_values","ctr","cpc","cpm","purchase_roas"])

Repeat for Campaign B.

Meta (period comparison): Same campaign, different time_range parameters.

Google Ads: google_ads_run_gaql(customer_id="...", query="SELECT campaign.name, metrics.cost_micros, metrics.impressions, metrics.clicks, metrics.conversions, metrics.conversions_value, metrics.ctr, metrics.average_cpc FROM campaign WHERE campaign.name LIKE '%CAMPAIGN_A%' AND segments.date DURING LAST_30_DAYS")

Read the full file on GitHub · 98 lines

Changes

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.

  1. 8d ago First seen · 98 lines · 28 tokens per session scan A 165bf3505507

Subscribe to this mod's changes

campaign-battle-report is a command published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 10d ago), licensed MIT. It adds 28 tokens to every session and 969 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.