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Professional PDF Ad Strategy Report Generator
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Basé sur la classification professionnelle SOC
Guided end-to-end execution of the paid-ads Blueprint produced by /ads-blueprint. Reads the existing ADS-Blueprint/ folder, detects the current phase, and coaches the user through every remaining step: closing blocking gaps, pixel & tracking setup, campaign build in each ad platform, launch day sequencing, learning-phase observation, and the bi-weekly optimization cycle (3× Kill Rule, 20% Scaling Rule, creative fatigue detection). Accepts pasted screenshots / CSV exports for live metric analysis. Produces platform-specific setup guides, a session log, and an HTML live dashboard. Use when user says execute my blueprint, help me launch, run my campaigns, post-launch optimization, scale my ads, audit my running campaigns, kill or scale decision, what should I do now with my ads, continue the blueprint, or invokes /ads-blueprint-execution.
End-to-end paid advertising skill for Claude Code: strategy generation, copy production, multi-platform audit, and client-ready reporting. Orchestrates 31 specialized sub-skills and 15 agents across Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, and Apple Ads. 250+ weighted checks, 11 industry templates, 5-agent parallel strategy builds, a guided zero-to-sales blueprint, a guided execution companion that takes you from blueprint to launched campaigns and ongoing optimization, PDF + HTML reports, and AI creative generation.
Guided, interactive end-to-end paid advertising blueprint. Walks the user through all 5 phases (Reality Check → Intelligence → Budget/Funnel → Creative → Landing/Test → Launch → Optimize) using one-question-at-a-time intake, checkpoint-style automation, adaptive explanations (beginner / intermediate / expert), and a clean folder-per-phase output structure. Produces a final recap, client-ready PDF, interactive HTML report, and a launch checklist. Use when user says start blueprint, guide me through ads, full ads setup, zero to sales, complete ad strategy from scratch, walk me through paid ads, or simply invokes /ads-blueprint.
Creative Brief Generator for designers, video editors, and content teams
60-Second Ad Readiness Snapshot — quick assessment without subagents
Full Ad Strategy Orchestrator. Launches 5 parallel subagents to build a complete advertising strategy from a single URL — audience personas, creative concepts, funnel architecture, competitive intelligence, and budget allocation. Produces a composite Ad Readiness Score (0-100) with a unified, client-ready strategy report.
| name | ads-report-pdf |
| description | Professional PDF Ad Strategy Report Generator |
| version | 1.0.0 |
| author | maxym-ai-ads |
| tags | ["ads","pdf","report","strategy","client-ready"] |
| trigger | /ads report-pdf |
| output | ADS-STRATEGY-REPORT.pdf |
Generate a polished, client-ready PDF advertising strategy report using the ReportLab Python library. This skill scans the current working directory for all ads output files, extracts scores, audience personas, campaign structure, budget allocation, and competitive intelligence, compiles them into structured JSON, and produces a professional PDF with a cover page featuring an Ad Readiness Score gauge, audience persona cards, campaign funnel diagram, budget allocation chart, competitive positioning map, creative direction summary, and a prioritized 90-day action plan.
/ads report-pdf or /ads report-pdf <business name>| Format | Best For | Pros | Cons |
|---|---|---|---|
| Client presentations, email attachments, proposals, sales collateral | Professional appearance, charts and gauges, printable, consistent formatting | Requires Python script, harder to edit | |
| Markdown | Internal use, quick reference, iterative editing, version control | Easy to edit, fast to generate, git-friendly | Less visually polished, no charts |
Rule of thumb: If the report goes to a client, prospect, or executive, use PDF. If it is for internal use or further editing, use Markdown.
First, check if the dedicated PDF generation script exists:
ls ~/.claude/skills/ads/scripts/generate_ads_pdf.py 2>/dev/null
If the script exists: Use it directly (skip to Step 4). If the script does not exist: Generate the PDF inline using ReportLab (follow all steps).
Scan the current working directory for all ads skill outputs. Search for these files:
Primary data sources (search for all of these):
ADS-STRATEGY-*.md — Full strategy report (composite scores, all sections)ADS-AUDIENCE*.md — Audience personas, targeting parametersADS-COPY-*.md — Platform-specific ad copyADS-HOOKS*.md — Scroll-stopping hooksADS-CREATIVE-BRIEF*.md — Creative briefs for all formatsADS-VIDEO-SCRIPTS*.md — Video ad scriptsADS-FUNNEL*.md — Campaign funnel architectureADS-BUDGET*.md — Budget allocation planADS-COMPETITORS*.md — Competitive intelligenceADS-KEYWORDS*.md — Keyword strategy (Google Ads)ADS-TESTING-PLAN*.md — A/B testing planADS-LANDING*.md — Landing page auditADS-AUDIT*.md — Performance audit resultsSearch command:
ls ADS-*.md 2>/dev/null
For each file found, extract:
Compile all extracted data into a structured JSON object for the PDF generator:
{
"report_metadata": {
"business_name": "[Business Name]",
"website_url": "[URL]",
"industry": "[Industry]",
"report_date": "[YYYY-MM-DD]",
"generated_by": "maxym-ai-ads"
},
"ad_readiness_score": {
"composite_score": 0,
"audience_clarity": {"score": 0, "weight": 25, "findings": []},
"creative_quality": {"score": 0, "weight": 20, "findings": []},
"funnel_architecture": {"score": 0, "weight": 20, "findings": []},
"competitive_position": {"score": 0, "weight": 15, "findings": []},
"budget_efficiency": {"score": 0, "weight": 20, "findings": []}
},
"audience_personas": [
{
"name": "[Persona Name]",
"age_range": "[Age Range]",
"role_title": "[Role/Title]",
"pain_points": [],
"motivations": [],
"platforms": [],
"targeting_params": {}
}
],
"campaign_structure": {
"funnel_stages": [],
"campaigns": [],
"retargeting_flows": []
},
"budget_allocation": {
"total_monthly_budget": 0,
"platform_split": {},
"funnel_stage_split": {},
"projected_metrics": {
"estimated_impressions": 0,
"estimated_clicks": 0,
"estimated_conversions": 0,
"projected_cpa": 0,
"projected_roas": 0
}
},
"competitive_intelligence": {
"competitors_analyzed": [],
"positioning_gaps": [],
"messaging_opportunities": []
},
"top_ad_copy": {
"best_hooks": [],
"top_headlines": [],
"best_ctas": []
},
"action_plan": {
"week_1": [],
"week_2_4": [],
"month_2_3": []
},
"critical_findings": [],
"quick_wins": []
}
Run the PDF generation script with the compiled JSON data:
python3 ~/.claude/skills/ads/scripts/generate_ads_pdf.py
If the script does not exist, generate it inline. The script must produce a PDF with these sections:
Page 1: Cover Page
Page 2: Executive Summary
Page 3: Audience Analysis
Page 4: Creative Direction
Page 5: Campaign Architecture
AWARENESS → CONSIDERATION → CONVERSION → RETENTION
[Campaign] [Campaign] [Campaign] [Campaign]
[Budget %] [Budget %] [Budget %] [Budget %]
Page 6: Competitive Positioning
Page 7: Budget Allocation
| Metric | Month 1 | Month 2 | Month 3 |
|---|---|---|---|
| Spend | $X | $X | $X |
| Impressions | X | X | X |
| Clicks | X | X | X |
| Conversions | X | X | X |
| CPA | $X | $X | $X |
| ROAS | Xx | Xx | Xx |
Page 8: 90-Day Action Plan
Page 9: Appendix (if data available)
/ads keywords was run)/ads copy was run)/ads landing was run)/ads testing was run)Layout:
Colors:
Typography:
Charts (ReportLab Drawing):
After generating the PDF:
ls -la ADS-STRATEGY-REPORT.pdf
Report the file size and location to the user
Suggest next steps:
/ads audit after 7 days of campaign dataNot all skills may have been run before generating the PDF. Handle gracefully:
| Data Available | Behavior |
|---|---|
| Full strategy run (all 5 agents) | Generate complete report with all pages |
| Partial data (some agents) | Generate report with available sections, mark missing sections as "Not Yet Analyzed" |
| Only quick snapshot | Generate a mini-report (cover + executive summary + action plan) |
| No data files found | Inform user to run /ads strategy <url> first |
Minimum required data: At least one ADS-*.md file must exist. If none are found, display:
No ad strategy data found in current directory.
Run '/ads strategy <url>' first to generate the analysis,
then use '/ads report-pdf' to create the PDF report.
The final output is a single PDF file: ADS-STRATEGY-REPORT.pdf
Saved to the current working directory alongside the Markdown source files.
pip3 install reportlabADS-STRATEGY-REPORT.pdf for consistency