Marketing analysis skills with a real analysis engine. Audit paid campaigns, find SEO opportunities, detect churn signals, and generate branded PDF reports — powered by 113 tested functions that handle the math deterministically.

Works with any data: connect the Dataslayer MCP for automatic data fetching from 50+ platforms, or paste your own CSV/JSON manually.

Compatible with Claude Desktop (Cowork), Claude Code, Cursor, Windsurf, and any agent that supports the Agent Skills spec.

• Installation — plugin vs individual skills, where and how
  • Plugin install (Cowork)
  • Individual skills (any plan)
  • Claude Code (terminal)
• Two ways to use
• What is Dataslayer
• Why this is different
• Skills overview
• ds-brain
• ds-report-pdf
• ds-paid-audit
• ds-channel-report
• ds-seo-weekly
• ds-content-perf
• ds-churn-signals
• Business context
• Quick start
• Supported platforms
• Contributing

Don't know which to choose? If you have Cowork, use the plugin — it's one download and you get everything. If not, install the individual skills you need.

Requires: Claude Desktop with a Cowork plan.

1. Download dataslayer-marketing-skills.zip

2. Open Claude Desktop → click Customize in the left sidebar

3. Under Personal plugins, click the + button → Upload plugin

   

4. Select the .zip file and click Upload

Done — all 7 skills, 4 agents, and the analysis engine are ready.

Note: The file must have a .zip extension — .plugin is not accepted (known issue).

Works on: claude.ai web and Claude Desktop — no Cowork required.

1. Download the skill you need from the table below

2. Go to Customize → Skills → + → Upload skill

   

3. Select the .zip file and click Upload

4. Repeat for each skill you want

Tip: Each .zip contains exactly one skill. The "Upload skill" dialog only accepts one SKILL.md per file.

Works on: Claude Code, Cursor, Windsurf.

git clone https://github.com/Dataslayer-AI/Marketing-skills.git
claude --plugin-dir ./Marketing-skills

/plugin marketplace add Dataslayer-AI/Marketing-skills
/plugin install dataslayer-marketing-skills@dataslayer-ai-marketing-skills

git clone https://github.com/Dataslayer-AI/Marketing-skills.git .marketing-skills-tmp

cp -r .marketing-skills-tmp/skills/*  .claude/skills/
cp -r .marketing-skills-tmp/agents/*  .claude/agents/
cp .marketing-skills-tmp/scripts/ds_utils.py .claude/scripts/

rm -rf .marketing-skills-tmp

Connect the Dataslayer MCP and the skills fetch your live data automatically. No exports, no copy-pasting.

You:    "Audit my Google Ads campaigns"
Claude: [fetches live data from Google Ads, Meta, GA4...]
        "Your Europe campaign has a CPA of €84 vs your €52 target.
         Here are 3 specific actions to fix it this week."

Setup: dataslayer.ai/mcp — takes ~5 minutes. Requires a Dataslayer Advanced plan or higher.

Don't have Dataslayer yet? The skills still work. Paste your data (CSV, TSV, JSON, or a table in the chat) and get the same analysis, same benchmarks, same recommendations.

You:    "Audit my Google Ads campaigns"
Claude: "I don't detect a Dataslayer MCP. You can set one up at
         dataslayer.ai/mcp for automatic data fetching.

         For now, paste or upload your campaign data and I'll
         run the same analysis. Required columns: campaign name,
         impressions, clicks, cost, conversions."

Same analysis engine. Same quality. Just less automation.

Dataslayer is a marketing data integration platform trusted by 2,000+ companies worldwide. It connects 50+ marketing platforms — Google Ads, Meta Ads, LinkedIn Ads, GA4, Search Console, TikTok Ads, and more — to destinations like Google Sheets, Looker Studio, BigQuery, Snowflake, and Excel.

Built by Softpoint, Dataslayer is ISO 27001 and ISO 27701 certified, independently audited for security and privacy.

The Dataslayer MCP is what makes these skills different: it gives Claude direct, live access to your marketing data — no exports, no copy-pasting, no stale CSVs.

Other marketing skills repos give Claude generic instructions. These skills include a tested analysis engine — ds_utils.py with 113 tests — that handles UTM stripping, page classification, MRR calculation, campaign pause detection, CPA sanity checks, and period comparison deterministically.

The analysis is the product. Whether data comes from Dataslayer MCP automatically or from a CSV you paste manually, the same engine runs: same benchmarks, same classifications, same actionable output.

With the Dataslayer MCP connected, it goes from good to effortless:

# Without Dataslayer MCP (still works):
You:    "Audit my Google Ads campaigns"
Claude: "Paste your campaign data — I need: campaign, spend, clicks, conversions"
You:    [pastes CSV]
Claude: "Your Europe campaign has a CPA of €84 vs your €52 target..."

# With Dataslayer MCP (zero friction):
You:    "Audit my Google Ads campaigns"
Claude: [fetches live data automatically]
        "Your Europe campaign has a CPA of €84 vs your €52 target..."

The repo also includes three development/QA tools (ds-lint, ds-eval, ds-audit) used for validating and testing skills. See CONTRIBUTING.md for details.

No other marketing skills repository does this today.

ds-brain launches four specialized subagents simultaneously. While every other skill analyzes one channel at a time, ds-brain runs paid, organic, content, and retention in parallel — and then finds the connections between them.

You: "Give me the full picture"

Claude launches 4 agents at once:
├── ds-agent-paid     → Google Ads, Meta, LinkedIn data
├── ds-agent-organic  → Search Console, GA4 organic
├── ds-agent-content  → Blog performance, conversions by page
└── ds-agent-retention → At-risk accounts, MRR at risk

Claude synthesizes all four and finds cross-channel patterns:

"Your paid CPA improved 18% this month — but retention data shows
accounts acquired in the same period have a 34% lower activation rate.
The algorithm found cheaper traffic. It's the wrong audience.
Every euro saved in acquisition is being lost twice in churn.

This week's priority: pause the Europe PMax campaign and audit
audience signals before reactivating."

One command. Four agents running simultaneously. One clear priority for the week.

Turn any analysis into a client-ready PDF with a single command.

ds-report-pdf fetches real data, analyzes it, writes Python code, executes it, and delivers a professional branded PDF — all automatically.

You never touch a config file unless you want to. Just tell Claude what you need:

"Generate the monthly report for Acme Corp.
Use their logo from https://acmecorp.com/logo.png,
brand color #1B2F6E, report in Spanish,
footer should say Prepared by Agency XYZ."

"Make it darker blue"
"Remove the retention section, not relevant for this client"
"Shorter — just 2 pages with the key numbers"
"Save these settings for Acme Corp"

Every preference is applied immediately and remembered for the rest of the session.

• Cover page — client logo, brand colors, report period, agency footer
• Executive summary — top-line metrics in a scannable card grid
• Channel performance — tables with current vs previous period, color-coded changes
• Key findings — max 3, each with what happened, why it matters, what to do
• Recommended actions — numbered, prioritized, with expected impact
• Page headers and footers — client name, agency name, page numbers

Step 1: "Give me the full picture"
        → ds-brain analyzes everything in parallel

Step 2: "Generate the client report for Acme Corp"
        → ds-report-pdf produces the branded PDF

Step 3: Send the PDF directly to your client.

Two commands. Zero manual work. One PDF ready to send.

Once you have the right setup for a client, say:

"Save these settings for Acme Corp"

Claude writes dataslayer-config.json automatically. Next month:

"Monthly report for Acme Corp"

That's it. Logo, colors, language, channels — all remembered.

Deep-dive into paid media campaigns. Detects budget traps, audience mismatches, creative fatigue, and conversion tracking issues.

You: "Audit my paid campaigns"

Claude: [fetches Google Ads + Meta + LinkedIn via MCP]

"AUDIENCE MISMATCH IN PMAX EUROPE · Severity: High

What is happening: 'Pet Food & Supplies' audience is generating 39% of
conversions at a CPA of €124, vs your target of €52.

Why it matters: You are spending €1,800/month on users unlikely to be
your ICP, inflating your blended CPA by ~35%.

What to do: Add 'Pet Food & Supplies' as a negative audience signal.
Monitor for 7 days."

Weekly cross-channel digest. Scans for anomalies (any metric moving ±25% week over week), forms hypotheses about the cause, and delivers a concise report with one clear "signal of the week."

Classifies your Search Console data into four buckets before writing anything:

• Quick wins — queries ranking 4–15 with >200 impressions. One content update away from page 1.
• CTR problems — ranking 1–10 but CTR below 3%. Fix the title, not the content.
• Ranking drops — positions lost >5 places. Immediate investigation needed.
• Conversion gaps — high traffic pages with conversion rate below 0.5%.

Separates content into four categories: stars (high traffic + high conversion), traffic without conversion, conversion without traffic (hidden gems), and neither. Tells you exactly what to publish next based on what the data shows actually converts.

Red / Amber / Green risk scoring for every active paid account. Surfaces MRR at risk before accounts cancel. Distinguishes between stated cancellation reason and real reason based on usage data.

"Stated reason: Too expensive
Usage data: 3 queries in 90 days, never ran a report
Real reason: Never got value. Price was the excuse, not the cause."

Every skill tries to load .agents/product-marketing-context.md automatically. This file tells Claude about your product, targets, and channels — so it can give relevant analysis instead of asking you setup questions every time.

To set it up (from the repo root):

cp .agents/product-marketing-context.example.md .agents/product-marketing-context.md
# Edit the file with your details

Without this file, skills still work — they'll just ask a fallback question on the first run.

"Give me the full picture"
→ ds-brain (4 parallel agents, all channels)

"Generate the monthly report for my client"
→ ds-report-pdf (branded PDF, ready to send)

"Audit my paid campaigns"
→ ds-paid-audit

"Weekly marketing summary"
→ ds-channel-report

"What are my best SEO opportunities this week?"
→ ds-seo-weekly

"Which blog posts are driving the most trials?"
→ ds-content-perf

"Which accounts are about to cancel?"
→ ds-churn-signals

Paid media (full audit support): Google Ads, Meta Ads (Facebook/Instagram), LinkedIn Ads

Paid media (basic metrics in cross-channel reports): TikTok Ads, Reddit Ads

Analytics: Google Analytics 4, Google Search Console

Retention: Stripe (subscription health, payment failures, churn signals)

Destinations: Google Sheets, Looker Studio, BigQuery, Snowflake, Excel

Dataslayer connects 50+ platforms — the skills above cover the channels with dedicated analysis logic. Other channels connected via Dataslayer will appear in raw data fetches but won't have skill-specific audit logic.

Full connector list at dataslayer.ai/connectors

Found a bug or want to add a skill? PRs and issues welcome.

See CONTRIBUTING.md for guidelines.

MIT — use freely.

Built by Dataslayer — the marketing data platform for teams that run on data.