A command for creating a paid-advertising dashboard comparing Google Ads and Meta Ads, two platforms used to promote products online.

Use it to show advertising spend, clicks, conversions, return on ad spend (revenue compared with advertising cost), click conversion rates, and campaign performance.

It ensures campaign figures come from the approved 90-day data and clearly labels differences between estimated and platform-reported results.

How eduardocornelsen/full-funnel-ai-analytics configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to eduardocornelsen/full-funnel-ai-analytics. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/eduardocornelsen/full-funnel-ai-analytics/main/.claude/commands/campaign.md

Clone the repo

git clone --depth 1 https://github.com/eduardocornelsen/full-funnel-ai-analytics

Made for: Claude Code.

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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/eduardocornelsen/full-funnel-ai-analytics/campaign/github.svg)](https://agentmods.dev/commands/eduardocornelsen/full-funnel-ai-analytics/campaign)

Your own site

<a href="https://agentmods.dev/commands/eduardocornelsen/full-funnel-ai-analytics/campaign"><img src="https://agentmods.dev/badge/commands/eduardocornelsen/full-funnel-ai-analytics/campaign/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.

Your own site · 80×15

<a href="https://agentmods.dev/commands/eduardocornelsen/full-funnel-ai-analytics/campaign"><img src="https://agentmods.dev/badge/commands/eduardocornelsen/full-funnel-ai-analytics/campaign.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 630 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.

Model	Per session	Once invoked
Fable 5.1	$0.00000	$0.00630
Opus 5	$0.00000	$0.00315
Sonnet 5	$0.00000	$0.00126
Haiku 4.5	$0.00000	$0.00063

Measured 10d ago against content hash ef61a226b2d0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

campaign 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 10d 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.

.claude/commands/campaign.md · 27 lines

How it starts

The opening of the file, as written. The whole thing — 27 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data sourcing (mandatory)

Read dashboards/golden_metrics.json → windowed_90d.campaigns (google and meta arrays) and copy exact values — never recalculate (CLAUDE.md §14).

Google ROAS is already canonical (conversions × $100 / cost); label Google est. · AOV $100.
Meta ROAS is platform-reported; label Meta platform.
CVRs in these tables are Click CVR — label CVR (click); never compare against Session CVR (§1).
Freshness badge in the header: _meta.window_start – _meta.window_end · Data as of _meta.generated_at.

Live MCP variant — only if the user appends -mcp or asks for "live" / "real-time" / "raw platform" data: query the google-ads, meta-ads MCP servers instead, passing dates from _meta.window_start / _meta.window_end, add the badge ⚡ Live MCP — may differ from golden layer, and use dashboards/js/metrics.js canonical formulas for any computed metric.

Artifact

Build a paid campaign performance React artifact using Recharts.

Design: dark theme (#0d0d1a bg, #1a1a2e cards), blue #60a5fa, coral #f87171, amber #fbbf24.

Include these 7 sections:

Platform comparison cards — Google Ads vs Meta Ads: Spend, Clicks, Conversions, ROAS side by side
Daily spend trend — dual-line chart: Google spend vs Meta spend over time
CTR vs CVR scatter — one dot per campaign, color = platform, size = spend
Campaign table — all campaigns sorted by ROAS: name, platform, spend, clicks, CTR, conversions, CVR, ROAS
Budget pacing bar — for each active campaign: spent vs estimated total budget as a horizontal progress bar
Recommendation callout — highlight which campaigns to scale (ROAS > 3x) and which to pause (ROAS < 1x)
AI Insights panel — a dark card at the bottom with a "✦ AI Insights" header containing 4–5 bullet points synthesized across both platforms. Each bullet must be specific, quantified, and actionable. Cover: (a) the single campaign with the highest ROAS that is under-budgeted — name it and estimate incremental revenue if budget were doubled, (b) the campaign(s) that should be paused immediately and why, (c) a platform-level efficiency comparison (Google vs Meta ROAS, CTR, CVR) with a clear reallocation recommendation, (d) a CTR or CVR anomaly worth investigating, (e) overall budget pacing status — whether spend is on track for the month. Write in plain English as if briefing a paid media manager.

Read the full file on GitHub · 27 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.

10d ago First seen · 27 lines · 0 tokens per session scan A ef61a226b2d0

Subscribe to this mod's changes

campaign is a command published in the GitHub repository eduardocornelsen/full-funnel-ai-analytics (21 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 630 tokens. 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 2026-08-30.

Analytics and metrics Marketing and SEO ai-analytics bigquery dbt-core duckdb genai mcp

full-funnel-ai-analytics: Command for Claude Code

Borrowing it

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

Data sourcing (mandatory)

Artifact

What this file has done since we first saw it

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