PDF Marketing Report Generator
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| 1 | # PDF Marketing Report GeneratorA5 — No allowed-tools declared — no way to tell what this skill may touchB3 — Frontmatter: no frontmatter |
| 2 | |
| 3 | ## Skill Purpose |
| 4 | 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. |
| 5 | |
| 6 | ## When to Use |
| 7 | - User wants a PDF version of the marketing report (not just Markdown) |
| 8 | - User is preparing a deliverable for a client presentation |
| 9 | - User asks for a "polished report", "client-ready report", or "PDF report" |
| 10 | - User wants a visual report with charts and scores |
| 11 | - Triggered by `/market report-pdf` or `/market report-pdf <domain>` |
| 12 | |
| 13 | ## When to Use PDF vs Markdown |
| 14 | |
| 15 | | Format | Best For | Pros | Cons | |
| 16 | |---|---|---|---| |
| 17 | | **PDF** | Client presentations, email attachments, sales collateral | Professional appearance, consistent formatting, visual charts, printable | Harder to edit, requires Python script | |
| 18 | | **Markdown** | Internal use, quick reference, iterative editing, version control | Easy to edit, readable in any editor, git-friendly | Less visually polished, no charts | |
| 19 | |
| 20 | **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. |
| 21 | |
| 22 | ## How to Execute |
| 23 | |
| 24 | ### Step 1: Collect All Available Data |
| 25 | Gather data from all previous skill runs. Check for these files in the project directory: |
| 26 | |
| 27 | **Primary data sources:** |
| 28 | - `MARKETING-AUDIT.md` -- Overall audit results |
| 29 | - `LANDING-CRO.md` -- Landing page conversion analysis |
| 30 | - `SEO-AUDIT.md` -- SEO findings |
| 31 | - `BRAND-VOICE.md` -- Brand voice analysis |
| 32 | - `COMPETITOR-ANALYSIS.md` -- Competitor comparison data |
| 33 | - `FUNNEL-ANALYSIS.md` -- Funnel analysis |
| 34 | - `SOCIAL-AUDIT.md` -- Social media audit |
| 35 | - `EMAIL-AUDIT.md` -- Email marketing audit |
| 36 | - `AD-AUDIT.md` -- Advertising audit |
| 37 | |
| 38 | **If no previous data exists:** |
| 39 | 1. Recommend the user run `/market audit <url>` first for the best results |
| 40 | 2. If the user insists on generating a report without prior audits, analyze the provided URL directly and build the data structure from scratch |
| 41 | 3. Use the analyze_page.py script to gather automated data: `python scripts/analyze_page.py <url>` |
| 42 | |
| 43 | ### Step 2: Build the JSON Data Structure |
| 44 | The `scripts/generate_pdf_report.py` script expects a JSON file as input with this exact structure: |
| 45 | |
| 46 | ```json |
| 47 | { |
| 48 | "url": "https://example.com", |
| 49 | "date": "March 1, 2026", |
| 50 | "brand_name": "Example Co", |
| 51 | "overall_score": 62, |
| 52 | "executive_summary": "A 2-4 sentence summary of the overall marketing health, key opportunities, and estimated revenue impact of implementing recommendations.", |
| 53 | "categories": { |
| 54 | "Content & Messaging": { |
| 55 | "score": 68, |
| 56 | "weight": "25%" |
| 57 | }, |
| 58 | "Conversion Optimization": { |
| 59 | "score": 52, |
| 60 | "weight": "20%" |
| 61 | }, |
| 62 | "SEO & Discoverability": { |
| 63 | "score": 74, |
| 64 | "weight": "20%" |
| 65 | }, |
| 66 | "Competitive Positioning": { |
| 67 | "score": 48, |
| 68 | "weight": "15%" |
| 69 | }, |
| 70 | "Brand & Trust": { |
| 71 | "score": 70, |
| 72 | "weight": "10%" |
| 73 | }, |
| 74 | "Growth & Strategy": { |
| 75 | "score": 55, |
| 76 | "weight": "10%" |
| 77 | } |
| 78 | }, |
| 79 | "findings": [ |
| 80 | { |
| 81 | "severity": "Critical", |
| 82 | "finding": "Description of the most important finding" |
| 83 | }, |
| 84 | { |
| 85 | "severity": "High", |
| 86 | "finding": "Description of a high-priority finding" |
| 87 | }, |
| 88 | { |
| 89 | "severity": "Medium", |
| 90 | "finding": "Description of a medium-priority finding" |
| 91 | }, |
| 92 | { |
| 93 | "severity": "Low", |
| 94 | "finding": "Description of a lower-priority finding" |
| 95 | } |
| 96 | ], |
| 97 | "quick_wins": [ |
| 98 | "First quick win action item", |
| 99 | "Second quick win action item", |
| 100 | "Third quick win action item" |
| 101 | ], |
| 102 | "medium_term": [ |
| 103 | "First medium-term action item", |
| 104 | "Second medium-term action item", |
| 105 | "Third medium-term action item" |
| 106 | ], |
| 107 | "strategic": [ |
| 108 | "First strategic action item", |
| 109 | "Second strategic action item", |
| 110 | "Third strategic action item" |
| 111 | ], |
| 112 | "competitors": [ |
| 113 | { |
| 114 | "name": "Competitor A", |
| 115 | "positioning": "Their market position", |
| 116 | "pricing": "Their pricing model", |
| 117 | "social_proof": "Their trust signals", |
| 118 | "content": "Their content approach" |
| 119 | }, |
| 120 | { |
| 121 | "name": "Competitor B", |
| 122 | "positioning": "Their market position", |
| 123 | "pricing": "Their pricing model", |
| 124 | "social_proof": "Their trust signals", |
| 125 | "content": "Their content approach" |
| 126 | } |
| 127 | ] |
| 128 | } |
| 129 | ``` |
| 130 | |
| 131 | ### Step 3: Field-by-Field Data Assembly Guide |
| 132 | |
| 133 | #### `url` (string, required) |
| 134 | The target website URL. Use the full URL including protocol. |
| 135 | |
| 136 | #### `date` (string, required) |
| 137 | The report generation date. Format: "Month DD, YYYY" (e.g., "March 1, 2026"). |
| 138 | |
| 139 | #### `brand_name` (string, required) |
| 140 | The company or brand name. Used in competitor comparison table headers. |
| 141 | |
| 142 | #### `overall_score` (integer, 0-100, required) |
| 143 | The weighted average of all category scores. Calculate as: |
| 144 | ``` |
| 145 | overall_score = (content * 0.25) + (conversion * 0.20) + (seo * 0.20) + (competitive * 0.15) + (brand * 0.10) + (growth * 0.10) |
| 146 | ``` |
| 147 | |
| 148 | #### `executive_summary` (string, required) |
| 149 | A 2-4 sentence summary covering: |
| 150 | - Current marketing health assessment |
| 151 | - Top 1-2 most impactful findings |
| 152 | - Estimated revenue impact of implementing recommendations |
| 153 | - Recommended first step |
| 154 | |
| 155 | Keep it concise and impactful. This appears on the cover page right below the score gauge. |
| 156 | |
| 157 | #### `categories` (object, required) |
| 158 | Exactly 6 categories with their scores. The categories map to these evaluation areas: |
| 159 | |
| 160 | | Category | What It Measures | Scoring Guidance | |
| 161 | |---|---|---| |
| 162 | | 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 | |
| 163 | | 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 | |
| 164 | | 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 | |
| 165 | | Competitive Positioning | Differentiation, pricing clarity, comparison content, market awareness | 80+: Clear positioning, comparison pages exist. 60-79: Some differentiation. <60: No clear positioning | |
| 166 | | Brand & Trust | Design quality, trust badges, security indicators, professional appearance | 80+: Modern design, trust signals throughout. 60-79: Adequate design. <60: Outdated or unprofessional | |
| 167 | | 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 | |
| 168 | |
| 169 | #### `findings` (array, required) |
| 170 | An array of finding objects, each with `severity` and `finding` fields. |
| 171 | |
| 172 | **Severity levels:** |
| 173 | - `Critical` -- Directly losing revenue or customers. Fix immediately. |
| 174 | - `High` -- Significant impact on growth. Fix within 1-2 weeks. |
| 175 | - `Medium` -- Meaningful improvement opportunity. Fix within 1 month. |
| 176 | - `Low` -- Nice-to-have improvement. Fix when time allows. |
| 177 | |
| 178 | **Writing effective findings:** |
| 179 | - Be specific: "Homepage headline says 'Welcome to Our Platform'" not "Headline needs improvement" |
| 180 | - Quantify impact: "Missing meta descriptions on 8 of 12 landing pages" |
| 181 | - Reference benchmarks: "Page load time is 4.2s (benchmark: under 2s)" |
| 182 | - Include evidence: "No testimonials found on homepage, pricing page, or signup page" |
| 183 | |
| 184 | Aim for 5-10 findings. Order from most to least severe. |
| 185 | |
| 186 | #### `quick_wins` (array, required) |
| 187 | 3-5 action items that can be implemented within one week with minimal effort. Each should be a specific, actionable instruction. |
| 188 | |
| 189 | **Good quick win:** "Rewrite the homepage headline from 'Welcome to Our Platform' to 'Cut Your Reporting Time by 75% -- Automated Analytics for Growth Teams'" |
| 190 | |
| 191 | **Bad quick win:** "Improve the headline" (too vague) |
| 192 | |
| 193 | #### `medium_term` (array, required) |
| 194 | 3-5 action items requiring 1-3 months to implement. These are more involved but have high impact. |
| 195 | |
| 196 | #### `strategic` (array, required) |
| 197 | 3-5 action items requiring 3-6 months. These are foundational changes that require planning and sustained effort. |
| 198 | |
| 199 | #### `competitors` (array, optional) |
| 200 | Up to 3 competitor objects for the comparison table. If no competitor data is available, omit this field -- the script will skip the competitor section. |
| 201 | |
| 202 | ### Step 4: Write the JSON File |
| 203 | Save the assembled data as a temporary JSON file: |
| 204 | |
| 205 | ```bash |
| 206 | # Write the JSON data to a temporary file |
| 207 | cat > /tmp/report_data.json << 'JSONEOF' |
| 208 | { |
| 209 | ... assembled JSON data ... |
| 210 | } |
| 211 | JSONEOF |
| 212 | ``` |
| 213 | |
| 214 | ### Step 5: Invoke the PDF Generator Script |
| 215 | |
| 216 | **Prerequisites check:** |
| 217 | First, verify that `reportlab` is installed: |
| 218 | ```bash |
| 219 | python3 -c "import reportlab" 2>/dev/null || pip3 install reportlab |
| 220 | ``` |
| 221 | |
| 222 | **Generate the report:** |
| 223 | ```bash |
| 224 | python3 scripts/generate_pdf_report.py /tmp/report_data.json "MARKETING-REPORT-<domain>.pdf" |
| 225 | ``` |
| 226 | |
| 227 | Replace `<domain>` with the target website's domain name (without protocol or www), using hyphens instead of dots. For example: |
| 228 | - `example.com` becomes `MARKETING-REPORT-example-com.pdf` |
| 229 | - `myapp.io` becomes `MARKETING-REPORT-myapp-io.pdf` |
| 230 | |
| 231 | **Demo mode (no arguments):** |
| 232 | Running the script without arguments generates a sample report with placeholder data: |
| 233 | ```bash |
| 234 | python3 scripts/generate_pdf_report.py |
| 235 | # Creates: MARKETING-REPORT-sample.pdf |
| 236 | ``` |
| 237 | |
| 238 | ### Step 6: Verify the Output |
| 239 | After generation, verify the PDF was created: |
| 240 | ```bash |
| 241 | ls -la "MARKETING-REPORT-<domain>.pdf" |
| 242 | ``` |
| 243 | |
| 244 | Report the file path and size to the user. |
| 245 | |
| 246 | ### Step 7: Clean Up |
| 247 | Remove the temporary JSON file: |
| 248 | ```bash |
| 249 | rm /tmp/report_data.json |
| 250 | ``` |
| 251 | |
| 252 | ## PDF Report Contents |
| 253 | |
| 254 | The generated PDF includes the following pages: |
| 255 | |
| 256 | ### Page 1: Cover Page |
| 257 | - Report title: "Marketing Audit Report" |
| 258 | - Target URL |
| 259 | - Generation date |
| 260 | - Overall score gauge (circular visualization with color coding) |
| 261 | - Grade letter (A+ through F) |
| 262 | - Executive summary paragraph |
| 263 | |
| 264 | ### Page 2: Score Breakdown |
| 265 | - Horizontal bar chart showing all 6 category scores with color coding |
| 266 | - Score table with category names, scores, weights, and status labels |
| 267 | - Color coding: Green (80+), Blue (60-79), Yellow (40-59), Red (<40) |
| 268 | |
| 269 | ### Page 3: Key Findings |
| 270 | - Findings table with severity labels and descriptions |
| 271 | - Color-coded severity indicators (Critical = red, High = orange, Medium = yellow, Low = blue) |
| 272 | - Findings ordered from most to least severe |
| 273 | |
| 274 | ### Page 4: Prioritized Action Plan |
| 275 | - Quick Wins section (This Week) |
| 276 | - Medium-Term section (1-3 Months) |
| 277 | - Strategic section (3-6 Months) |
| 278 | - Numbered action items in each tier |
| 279 | |
| 280 | ### Page 5: Competitive Landscape (if competitor data provided) |
| 281 | - Comparison table with client vs up to 3 competitors |
| 282 | - Rows: Positioning, Pricing, Social Proof, Content |
| 283 | |
| 284 | ### Final Page: Methodology |
| 285 | - Scoring methodology explanation |
| 286 | - Category weights and measurement criteria |
| 287 | - Footer: "Generated by AI Marketing Suite for Claude Code" |
| 288 | |
| 289 | ## Color Scheme |
| 290 | |
| 291 | The PDF uses a professional color palette: |
| 292 | |
| 293 | | Element | Color | Hex Code | |
| 294 | |---|---|---| |
| 295 | | Primary (headers, titles) | Dark Navy | #1B2A4A | |
| 296 | | Accent (links, highlights) | Blue | #2D5BFF | |
| 297 | | Highlight (attention) | Orange | #FF6B35 | |
| 298 | | Success (high scores) | Green | #00C853 | |
| 299 | | Warning (medium scores) | Amber | #FFB300 | |
| 300 | | Danger (low scores, critical) | Red | #FF1744 | |
| 301 | | Light background | Light Gray | #F5F7FA | |
| 302 | | Body text | Dark Gray | #2C3E50 | |
| 303 | | Secondary text | Medium Gray | #7F8C9B | |
| 304 | | Borders | Light Border | #E0E6ED | |
| 305 | |
| 306 | ## Score-to-Color Mapping |
| 307 | - 80-100: Green (#00C853) -- Strong performance |
| 308 | - 60-79: Blue (#2D5BFF) -- Solid with room to improve |
| 309 | - 40-59: Amber (#FFB300) -- Needs attention |
| 310 | - 0-39: Red (#FF1744) -- Critical issues |
| 311 | |
| 312 | ## Troubleshooting |
| 313 | |
| 314 | | Issue | Solution | |
| 315 | |---|---| |
| 316 | | `ModuleNotFoundError: No module named 'reportlab'` | Run `pip3 install reportlab` | |
| 317 | | Script produces empty PDF | Check that JSON data has all required fields | |
| 318 | | Score gauge not rendering | Ensure `overall_score` is a number 0-100 | |
| 319 | | Competitor table missing | Ensure `competitors` array has objects with `name`, `positioning`, `pricing`, `social_proof`, `content` fields | |
| 320 | | PDF is only 1 page | Check for JSON parsing errors -- run `python3 -c "import json; json.load(open('/tmp/report_data.json'))"` | |
| 321 | | Fonts look wrong | The script uses Helvetica (built into reportlab). No custom fonts needed. | |
| 322 | |
| 323 | ## Integration with Other Skills |
| 324 | |
| 325 | This skill works best when combined with other audit skills. The recommended workflow: |
| 326 | |
| 327 | 1. Run `/market audit <url>` -- Generates comprehensive audit data |
| 328 | 2. Run `/market competitors <url>` -- Adds competitor comparison data |
| 329 | 3. Run `/market seo <url>` -- Adds detailed SEO findings |
| 330 | 4. Run `/market landing <url>` -- Adds CRO analysis |
| 331 | 5. Run `/market report-pdf <url>` -- Compiles everything into a PDF |
| 332 | |
| 333 | The PDF report skill will automatically look for output files from these skills and incorporate their data into the report JSON. |
| 334 | |
| 335 | ## Output |
| 336 | - **File:** `MARKETING-REPORT-<domain>.pdf` |
| 337 | - **Location:** Project root directory |
| 338 | - **Size:** Typically 200KB-500KB depending on content volume |
| 339 | - **Pages:** 5-7 pages depending on whether competitor data and additional sections are included |
| 340 | |
| 341 | ## Key Principles |
| 342 | - The PDF report is the most client-facing deliverable in the toolkit. Quality matters. |
| 343 | - Always verify the JSON data is complete and accurate before generating. Garbage in, garbage out. |
| 344 | - Use the PDF for initial client impressions and sales conversations. Follow up with the more detailed Markdown report if the client engages. |
| 345 | - Every score should be justifiable. If a client asks "why did I get a 52 in Conversion Optimization?", the findings should provide clear evidence. |
| 346 | - Round scores to whole numbers. Decimals imply false precision. |
| 347 | - Keep the executive summary tight -- 2-4 sentences maximum. Clients skim cover pages. |
| 348 | - If generating for a prospect (not yet a client), the report serves as a sales tool. Make the opportunities compelling and the action plan achievable. |
| 349 |
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