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>
Step 2: Build the JSON Data Structure
The scripts/generate_pdf_report.py script expects a JSON file as input with this exact structure:
{
"url": "https://example.com",
"date": "March 1, 2026",
"brand_name": "Example Co",
"overall_score": 62,
"executive_summary": "A 2-4 sentence summary of the overall marketing health, key opportunities, and estimated revenue impact of implementing recommendations.",
"categories": {
"Content & Messaging": {
"score": 68,
"weight": "25%"
},
"Conversion Optimization": {
"score": 52,
"weight": "20%"
},
"SEO & Discoverability": {
"score": 74,
"weight": "20%"
},
"Competitive Positioning": {
"score": 48,
"weight": "15%"
},
"Brand & Trust": {
"score": 70,
"weight": "10%"
},
"Growth & Strategy": {
"score": 55,
"weight": "10%"
}
},
"findings": [
{
"severity": "Critical",
"finding": "Description of the most important finding"
},
{
"severity": "High",
"finding": "Description of a high-priority finding"
},
{
"severity": "Medium",
"finding": "Description of a medium-priority finding"
},
{
"severity": "Low",
"finding": "Description of a lower-priority finding"
}
],
"quick_wins": [
"First quick win action item",
"Second quick win action item",
"Third quick win action item"
],
"medium_term": [
"First medium-term action item",
"Second medium-term action item",
"Third medium-term action item"
],
"strategic": [
"First strategic action item",
"Second strategic action item",
"Third strategic action item"
],
"competitors": [
{
"name": "Competitor A",
"positioning": "Their market position",
"pricing": "Their pricing model",
"social_proof": "Their trust signals",
"content": "Their content approach"
},
{
"name": "Competitor B",
"positioning": "Their market position",
"pricing": "Their pricing model",
"social_proof": "Their trust signals",
"content": "Their content approach"
}
]
}
Step 3: Field-by-Field Data Assembly Guide
url (string, required)
The target website URL. Use the full URL including protocol.
date (string, required)
The report generation date. Format: "Month DD, YYYY" (e.g., "March 1, 2026").
brand_name (string, required)
The company or brand name. Used in competitor comparison table headers.
overall_score (integer, 0-100, required)
The weighted average of all category scores. Calculate as:
overall_score = (content * 0.25) + (conversion * 0.20) + (seo * 0.20) + (competitive * 0.15) + (brand * 0.10) + (growth * 0.10)
executive_summary (string, required)
A 2-4 sentence summary covering:
- Current marketing health assessment
- Top 1-2 most impactful findings
- Estimated revenue impact of implementing recommendations
- Recommended first step
Keep it concise and impactful. This appears on the cover page right below the score gauge.
categories (object, required)
Exactly 6 categories with their scores. The categories map to these evaluation areas:
| Category | What It Measures | Scoring Guidance |
|---|---|---|
| Content & Messaging | Copy quality, value proposition, headline clarity, CTA text, brand voice consistency | 80+: Clear, benefit-driven, specific. 60-79: Adequate but generic. <60: Vague, feature-focused, unclear |
| Conversion Optimization | Social proof, form design, CTA placement, objection handling, urgency | 80+: Multiple proof types, optimized forms, clear CTAs. 60-79: Some elements present. <60: Missing critical elements |
| SEO & Discoverability | Title tags, meta descriptions, headers, schema, internal linking, page speed | 80+: Fully optimized. 60-79: Mostly present with gaps. <60: Major issues or missing elements |
| Competitive Positioning | Differentiation, pricing clarity, comparison content, market awareness | 80+: Clear positioning, comparison pages exist. 60-79: Some differentiation. <60: No clear positioning |
| Brand & Trust | Design quality, trust badges, security indicators, professional appearance | 80+: Modern design, trust signals throughout. 60-79: Adequate design. <60: Outdated or unprofessional |
| Growth & Strategy | Lead capture, email marketing, content strategy, acquisition channels | 80+: Multi-channel strategy in place. 60-79: Some channels active. <60: No clear growth strategy |
findings (array, required)
An array of finding objects, each with severity and finding fields.
Severity levels:
Critical-- Directly losing revenue or customers. Fix immediately.High-- Significant impact on growth. Fix within 1-2 weeks.Medium-- Meaningful improvement opportunity. Fix within 1 month.Low-- Nice-to-have improvement. Fix when time allows.
Writing effective findings:
- Be specific: "Homepage headline says 'Welcome to Our Platform'" not "Headline needs improvement"
- Quantify impact: "Missing meta descriptions on 8 of 12 landing pages"
- Reference benchmarks: "Page load time is 4.2s (benchmark: under 2s)"
- Include evidence: "No testimonials found on homepage, pricing page, or signup page"
Aim for 5-10 findings. Order from most to least severe.
quick_wins (array, required)
3-5 action items that can be implemented within one week with minimal effort. Each should be a specific, actionable instruction.
Good quick win: "Rewrite the homepage headline from 'Welcome to Our Platform' to 'Cut Your Reporting Time by 75% -- Automated Analytics for Growth Teams'"
Bad quick win: "Improve the headline" (too vagu