\r \r

Daily News Reporter\r

\r AI-Assisted international news reporting toolkit with structured workflows and multi-source verification.\r \r

⚠️ Important Clarification\r

\r This skill is NOT a fully automated/unattended system. It operates as an AI-assisted workflow toolkit:\r \r | Component | What It Does | Who/What Executes |\r |-----------|--------------|-------------------|\r | news_collector.py | Data models, source classification, verification logic | AI Agent uses these structures |\r | generate_pdf.py | Converts Markdown reports to PDF | Runs automatically |\r | SKILL.md | Workflow instructions for AI | AI follows these guidelines |\r | Web Search | Actual information gathering | AI Agent executes via search tools |\r | Analysis | Content analysis and insight generation | AI Agent performs |\r \r Bottom line: This skill provides the framework and tools for professional news reporting, but requires an AI agent with web search capabilities to perform the actual data collection and analysis.\r \r

Overview\r

\r This skill provides structured workflows and utilities for generating professional daily international affairs reports:\r \r

1. Structured Information Collection - Tiered source system and verification frameworks\r
2. Source Verification Guidelines - Cross-reference methodologies and reliability indicators \r
3. Content Analysis Framework - Impact assessment and trend analysis guidelines\r
4. Report Generation Tools - Markdown-to-PDF conversion and templates\r \r

When to Use\r

\r Use this skill when:\r

• You need structured workflows for international news reporting\r
• You want consistent multi-tier source verification (Tier 1-4 system)\r
• You need professional PDF report generation from Markdown\r
• You want standardized templates for daily news summaries\r
• You're an AI agent helping a user generate news reports\r \r Do NOT expect: Fully automated, unattended 24/7 news monitoring without AI involvement.\r \r

Core Workflow (AI-Executed)\r

\r

Step 1: Information Collection (AI Agent Executes)\r

\r The AI agent performs web searches using the tiered source guidance:\r \r Search Guidance for AI:\r

• Use web search tools to query current news\r
• Prioritize Tier 1 sources when available\r
• Collect 6-10 sources across different tiers\r
• Document source URLs and timestamps\r \r Tier 1 - Official/International Organizations (Reliability: 5/5)\r
• UN News (news.un.org)\r
• International Maritime Organization (imo.org)\r
• Central bank official statements (federalreserve.gov, etc.)\r
• Government foreign ministry statements\r \r Tier 2 - Professional Financial Media (Reliability: 4-5/5)\r
• Bloomberg, Reuters, CNBC\r
• Trading Economics\r
• 金十数据 (for Chinese market perspective)\r \r Tier 3 - Mainstream International Media (Reliability: 4/5)\r
• CNN, BBC, AP News\r
• Major national news outlets\r \r Tier 4 - Regional/Industry Sources (Reliability: 2-3/5)\r
• Local news for specific regions\r
• Industry publications\r
• Use with caution, require verification\r \r Recommended Search Queries:\r

"[Date] international news global hot topics"\r
"[Organization] latest statement [topic]"\r
"[Market/commodity] price [date] latest"\r
"site:un.org [topic]"  # For official sources\r
"site:federalreserve.gov latest"\r
```\r
\r
### Step 2: Information Processing (AI Agent Executes)\r
\r
**Source Verification (AI performs):**\r
- Cross-reference key facts across minimum 2 independent sources\r
- Prioritize Tier 1 sources for critical information\r
- Flag information from Tier 3-4 sources with reliability indicators\r
- Use `news_collector.py` data structures to organize sources\r
\r
**Structured Information Format:**\r
```\r
Event:\r
  - Time: [timestamp with timezone]\r
  - Location: [specific location]\r
  - Key Actors: [entities involved]\r
  - Verified Facts: [from Tier 1-2 sources]\r
  - Context: [background from multiple sources]\r
  - Impact: [market/geopolitical analysis]\r
```\r
\r
### Step 3: Content Analysis (AI Agent Executes)\r
\r
**Impact Assessment Framework:**\r
| Severity | Criteria | Examples |\r
|----------|----------|----------|\r
| ⭐⭐⭐⭐⭐ | Global impact, major powers involved, market shock | War escalation, central bank policy shifts |\r
| ⭐⭐⭐⭐ | Regional impact, economic consequences | Energy supply disruptions, trade conflicts |\r
| ⭐⭐⭐ | Localized but significant | National policy changes, major corporate events |\r
| ⭐⭐ | Limited impact | Routine diplomatic activities |\r
| ⭐ | Minor interest | Local news, minor incidents |\r
\r
**Trend Analysis Guidelines:**\r
- Identify patterns across multiple events\r
- Compare with historical precedents\r
- Assess trajectory (escalating/stable/de-escalating)\r
\r
### Step 4: Report Generation (AI + Scripts)\r
\r
**AI Actions:**\r
1. Populate report template with collected data\r
2. Apply source attribution tags ([Official], [Professional], etc.)\r
3. Write analysis and insights\r
4. Save as Markdown file\r
\r
**Automated Script Execution:**\r
```bash\r
# Convert Markdown to PDF (runs automatically)\r
python scripts/generate_pdf.py --input report.md --output report.pdf\r
```\r
\r
## Source Reliability Framework\r
\r
### Tier 1 - Official/International (Reliability: 5/5)\r
- **Use for:** Critical facts, official statements, verified data\r
- **Examples:** UN agencies, central banks, government statements\r
- **Attribution tag:** [Official], [Organization name]\r
\r
### Tier 2 - Professional Financial (Reliability: 4-5/5)\r
- **Use for:** Market data, economic analysis, policy interpretation\r
- **Examples:** Bloomberg, Reuters, Trading Economics\r
- **Attribution tag:** [Professional], [Source name]\r
\r
### Tier 3 - Mainstream Media (Reliability: 4/5)\r
- **Use for:** Event coverage, general news, context\r
- **Examples:** CNN, BBC, major national outlets\r
- **Attribution tag:** [International], [Source name]\r
\r
### Tier 4 - Regional/Industry (Reliability: 2-3/5)\r
- **Use for:** Supplementary context, specific angles\r
- **Examples:** Local news, industry blogs\r
- **Attribution tag:** [Regional/Industry], [Source name], verification recommended\r
\r
## Scripts and Utilities\r
\r
### news_collector.py\r
**Purpose:** Data models and structures for source management\r
**Usage:**\r
```python\r
from scripts.news_collector import NewsCollector, NewsItem, NewsSource\r
\r
collector = NewsCollector()\r
sources = collector.get_sources_by_topic('energy')\r
# Use data structures to organize collected information\r
```\r
**Note:** This is a data structure utility, NOT an automated web scraper.\r
\r
### generate_pdf.py\r
**Purpose:** Convert Markdown reports to professionally formatted PDF\r
**Usage:**\r
```bash\r
python scripts/generate_pdf.py --input report.md --output report.pdf\r
```\r
**Note:** This runs automatically, no AI involvement required.\r
\r
### Source Directory (references/source_directory.md)\r
**Purpose:** Reference list of recommended information sources\r
**Usage:** AI consults this when planning search strategy\r
\r
## Report Templates\r
\r
Templates available in `assets/templates/`:\r
- `daily_report_template.md` - Standard daily report format with placeholders\r
- Use as starting point, AI fills in content\r
\r
## Best Practices for AI Agents\r
\r
1. **Always verify critical information** across at least 2 Tier 1-2 sources\r
2. **Timestamp all data** with timezone and source publication time\r
3. **Distinguish facts from analysis** - clearly label opinions/forecasts\r
4. **Include contradictory information** when sources disagree, with attribution\r
5. **Update risk assessments** based on new developments\r
6. **Archive sources** - maintain links/references for fact-checking\r
7. **Be honest about limitations** - acknowledge when information is incomplete\r
\r
## Quality Checklist\r
\r
Before finalizing report:\r
- [ ] All Tier 1 facts verified with official sources\r
- [ ] Market data from Tier 2 financial sources\r
- [ ] Impact ratings justified with evidence\r
- [ ] Contradictory information noted\r
- [ ] Source attribution complete with tier tags\r
- [ ] Timestamps accurate\r
- [ ] PDF generated successfully\r
- [ ] No placeholder text remaining\r
- [ ] Clear distinction between facts and AI analysis\r
\r
## Limitations and Disclaimers\r
\r
### System Limitations\r
- **NOT unattended/fully automated** - Requires AI agent for data collection\r
- Information delayed by search indexing (typically 1-2 hours)\r
- Cannot access paywalled content\r
- Language limitations for non-English/non-Chinese sources\r
\r
### Content Limitations\r
- Analysis based on publicly available information\r
- Predictions subject to rapid change in volatile situations\r
- No real-time data feeds - relies on search tools\r
- Source availability depends on search engine indexing\r
\r
### Appropriate Use\r
- ✅ AI-assisted research and reporting\r
- ✅ Structured news summaries\r
- ✅ Educational/analytical purposes\r
- ✅ Personal information aggregation\r
\r
### Inappropriate Use\r
- ❌ Unattended automated news service\r
- ❌ Real-time trading decisions without verification\r
- ❌ Replacement for professional journalism\r
- ❌ Source of truth for critical decisions without human review\r
\r
## Example Usage\r
\r
**User Request:** "Generate today's international news report"\r
\r
**AI Agent Execution:**\r
1. Read SKILL.md to understand workflow\r
2. Use web search tools to query current news (6-10 sources)\r
3. Apply tiered verification framework\r
4. Structure information using news_collector.py patterns\r
5. Write analysis following impact assessment guidelines\r
6. Generate Markdown using template\r
7. Run generate_pdf.py to create PDF\r
8. Present both formats to user\r
\r
**Output:** Professional daily report in Markdown and PDF formats\r
\r
## Technical Requirements\r
\r
### For AI Agent\r
- Web search capability (web_search tool or equivalent)\r
- Ability to read and execute Python scripts\r
- Markdown processing capability\r
- PDF viewing/verification capability\r
\r
### For Script Execution\r
- Python 3.8+\r
- reportlab library (`pip install reportlab`)\r
- Standard library only for news_collector.py\r
\r
## Files Included\r
\r
```\r
daily-news-reporter/\r
├── SKILL.md                          # This file - workflow instructions\r
├── scripts/\r
│   ├── news_collector.py            # Data structures (not a scraper)\r
│   └── generate_pdf.py              # PDF generation tool\r
├── references/\r
│   └── source_directory.md          # Source reference list\r
└── assets/\r
    └── templates/\r
        └── daily_report_template.md # Report template\r
```\r
\r
## License and Attribution\r
\r
This skill provides frameworks and tools for news reporting.\r
Users are responsible for:\r
- Verifying information accuracy\r
- Complying with source website terms of service\r
- Proper attribution of quoted sources\r
- Responsible use of generated content\r
\r
## Summary\r
\r
| Feature | Status | Notes |\r
|---------|--------|-------|\r
| Automated PDF generation | ✅ Yes | `generate_pdf.py` |\r
| Structured workflows | ✅ Yes | SKILL.md guidelines |\r
| Source tiering framework | ✅ Yes | Tier 1-4 system |\r
| **Automated web scraping** | ❌ **No** | **AI performs searches** |\r
| **Unattended 24/7 operation** | ❌ **No** | **Requires AI agent** |\r
| Real-time data feeds | ❌ No | Search-based only |\r
\r
**Bottom line:** This is an AI-assisted toolkit, not a fully autonomous news bot.\r