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Report Generator Adarsh

Report Generator Skill

adarshvmore0 来源安装数☆ 0 仓库 Stars

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

SkillHub CLI

skillhub install adarshvmore/report-generator-adarsh

打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

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

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

Output Schema

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

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

来源信息

Source
github
Repository
openclaw/skills
Path
skills/adarshvmore/report-generator-adarsh
Version
—
Commit
363a8b5671d7eee547327a345c43fe24be54f77d
分类来源
rules
状态
active
可见性
public

这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。

来源内容

SKILL.md
# 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

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