AI Marketing Suite for Claude Code is a collection of marketing skills and parallel agents that analyze websites and produce copy, email sequences, campaigns, content calendars, competitor research, and reports. Entrepreneurs, agencies, and solo operators use it to run marketing workflows from Claude Code, and the catalogue lists the suite's skills and agents.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/zubair-trabzada/ai-marketing-claudenpx agentmods add skills/zubair-trabzada/ai-marketing-claude/market-report-pdfWrote 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/skills/zubair-trabzada/ai-marketing-claude/market-report-pdf)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-marketing-claude/market-report-pdf"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-marketing-claude/market-report-pdf/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/skills/zubair-trabzada/ai-marketing-claude/market-report-pdf"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-marketing-claude/market-report-pdf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 249 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.03421 |
| Opus 5 | $0.00000 | $0.01710 |
| Sonnet 5 | $0.00000 | $0.00684 |
| Haiku 4.5 | $0.00000 | $0.00342 |
Grade A, and why
market-report-pdf 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 13d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- market-report-pdf — 97% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 349 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Marketing Report Generator
Skill Purpose
Generate a professional, visually polished PDF marketing report using the Python script scripts/generate_pdf_report.py. This skill collects all available audit and analysis data, structures it into the expected JSON format, invokes the script, and produces a branded PDF with score gauges, bar charts, comparison tables, findings, and a prioritized action plan.
When to Use
- User wants a PDF version of the marketing report (not just Markdown)
- User is preparing a deliverable for a client presentation
- User asks for a "polished report", "client-ready report", or "PDF report"
- User wants a visual report with charts and scores
- Triggered by
/market report-pdfor/market report-pdf <domain>
When to Use PDF vs Markdown
| Format | Best For | Pros | Cons |
|---|---|---|---|
| Client presentations, email attachments, sales collateral | Professional appearance, consistent formatting, visual charts, printable | Harder to edit, requires Python script | |
| Markdown | Internal use, quick reference, iterative editing, version control | Easy to edit, readable in any editor, git-friendly | Less visually polished, no charts |
Rule of thumb: If the report is going to a client or prospect, use PDF. If it is for internal use or further editing, use Markdown.
How to Execute
Step 1: Collect All Available Data
Gather data from all previous skill runs. Check for these files in the project directory:
Primary data sources:
MARKETING-AUDIT.md-- Overall audit resultsLANDING-CRO.md-- Landing page conversion analysisSEO-AUDIT.md-- SEO findingsBRAND-VOICE.md-- Brand voice analysisCOMPETITOR-ANALYSIS.md-- Competitor comparison dataFUNNEL-ANALYSIS.md-- Funnel analysisSOCIAL-AUDIT.md-- Social media auditEMAIL-AUDIT.md-- Email marketing auditAD-AUDIT.md-- Advertising audit
If no previous data exists:
- Recommend the user run
/market audit <url>first for the best results - If the user insists on generating a report without prior audits, analyze the provided URL directly and build the data structure from scratch
- Use the analyze_page.py script to gather automated data:
python scripts/analyze_page.py <url>
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.
- 13d ago First seen · 349 lines · 0 tokens per session scan A 32ca5b9158ba
market-report-pdf is a skill published in the GitHub repository zubair-trabzada/ai-marketing-claude (2,639 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,421 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.
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