Report Generator Adarsh

Generates a structured marketing audit report from aggregated data using a single GPT-4.1-mini API call with six predefined sections.

Report Generator Skill

Purpose

Single GPT-4.1-mini call that transforms aggregated marketing data into a structured, professional audit report. This is the ONLY AI call in the entire audit pipeline.

Input Schema

typescript

interface AuditData {
 input: AuditInput;
 instagram: InstagramData;
 metaAds: MetaAdsData;
 keywords: KeywordData;
 competitors: CompetitorData;
 websiteAudit: WebsiteAuditData;
 collectedAt: string;
}

Output Schema

typescript

interface MarketingReport {
 brand: string;
 generatedAt: string;
 sections: ReportSections;
 rawData: AuditData;
 reportMarkdown: string;
}

API Dependencies

• API: OpenAI
• Model: gpt-4.1-mini
• Auth: OPENAI_API_KEY
• Cost: ~$0.001-0.002 per call

Implementation Pattern

• System prompt defines the analyst persona and exact 6-section format
• User message is the full AuditData JSON
• Single API call with max_tokens: 1500, temperature: 0.4
• Response markdown is parsed into individual sections via ## header splitting
• Token usage is logged for cost tracking
• Fallback report is generated if OpenAI call fails

Token Budget

• Input: ~1,500-2,000 tokens (JSON data)
• Output: ~800-1,200 tokens (report)

Error Handling

• Missing API key: returns fallback report with error message
• API failure: returns fallback report with raw data preserved
• All errors logged with context

Example Usage

typescript

const report = await generateMarketingReport(auditData);
console.log(report.reportMarkdown);

Notes

• This is the ONLY file that should make OpenAI calls (except competitor collector fallback)
• Never add additional GPT calls to other modules