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Public opinion monitoring and structured report generation. Collects publicly available web information about celebrities, TV shows, or brands, performs sent...
---
name: sentiment-monitor
version: "0.3.1"
license: MIT
description: >
Public opinion monitoring and structured report generation.
Collects publicly available web information about celebrities, TV shows, or brands,
performs sentiment analysis, and generates responsive HTML reports.
Trigger keywords: sentiment, public opinion, reputation, monitoring report.
Examples: "monitor reputation of X", "public opinion analysis for X".
---
# Public Opinion Monitoring & Report Generation
This skill provides a structured methodology for monitoring and analyzing public sentiment about public-facing entities (celebrities, entertainment products, brands) using publicly available web information.
## Purpose & Scope
- **Input**: A target entity name and optional time range
- **Output**: A self-contained HTML report with sentiment analysis, event timeline, and actionable recommendations
- **Data sources**: Public web pages, news articles, social media (public content only)
- **Output format**: HTML file with embedded CSS (no external dependencies)
## Prerequisites
This skill requires the AI assistant platform to provide the following built-in tools:
| Tool | Role | Required |
|------|------|----------|
| WebSearch | Retrieve public web information | Yes |
| WebFetch | Read detailed web page content | Yes |
| Write | Save the generated HTML report | Yes |
| preview_url | Display the HTML report preview | Optional |
| deliver_attachments | Deliver the report file to the user | Optional |
> **Note**: If the platform does not provide WebSearch or WebFetch, this skill cannot function.
> In that case, inform the user that the required web access tools are not available.
This skill has **zero external dependencies**. It does not install packages, execute scripts, access system files, or communicate with external servers.
## Privacy & Data Policy
- All data comes from **publicly accessible web sources** only
- No private data, personal information, or non-public content is accessed
- Aggregate statistics (e.g., view counts, play counts) are only collected when explicitly displayed on public pages
- Missing data is labeled as "Data Unavailable" in reports — **no data is fabricated or estimated**
- Reports are saved to the user's local workspace; no data leaves the local environment
## Data Availability Caveats
> **Important context for agents**:
>
> The skill instructs gathering platform metrics (social media trending, view counts, engagement data).
> In practice, most specific numerical metrics (e.g., exact view counts, follower numbers) are only accessible
> through platform-specific APIs and are typically **not available** via public web search or page fetching.
>
> The agent should:
> - Only report metrics that are **explicitly visible** in the web search results or fetched page content
> - Never estimate, extrapolate, or fabricate numerical data
> - Use qualitative descriptions (e.g., "high activity", "significant engagement") when exact numbers are unavailable
> - Label any unavailable data as "Data Unavailable"
## Trigger Conditions
This skill activates when user requests include keywords related to:
- Public opinion, sentiment, reputation monitoring
- Celebrity or brand image analysis
- Media coverage or buzz tracking
## Supported Monitoring Targets
- **Entertainment figures**: Actors, musicians, influencers
- **Media products**: TV series, films, variety shows
- **Brands and products**: Consumer brands, product launches
## Workflow
### Phase 1: Parameter Identification
Extract from the user request:
| Parameter | Default | Description |
|-----------|---------|-------------|
| Target | User-specified | Name of the entity to monitor |
| Time range | Last 30 days | Customizable by user |
| Output format | HTML | Only HTML format is supported |
| Focus areas | All dimensions | Fan data, reputation events, platform activity, risk alerts |
### Phase 2: Public Information Gathering
The AI assistant gathers information from publicly accessible web sources across these dimensions:
**Basic data** (3-5 searches recommended):
- Recent news coverage
- Trending topics and hot searches
- Public reviews and discussions
- Fan community activity
- Cross-platform discussion volume
**Event identification**:
- Positive events: product releases, awards, charity work
- Negative events: controversies, criticism, backlash
- For each event: timestamp, platform, sentiment direction
> **Important**: Only data obtainable through public web searches should be used.
> If specific numerical data is unavailable, the report should indicate "Data Unavailable".
### Phase 3: Analysis
**3.1 Sentiment Classification**
Categorize the overall public opinion into:
- Positive proportion (favorable coverage, support, enthusiasm)
- Neutral proportion (objective reporting, general discussion)
- Negative proportion (criticism, controversy, backlash)
**3.2 Event Timeline**
Organize major events chronologically (minimum 5 events), including:
- Event name and description
- Timestamp
- Sentiment direction (positive / neutral / negative)
- Impact level (high / medium / low)
**3.3 Risk Assessment**
Identify current or potential reputation risks:
- Active negative sentiment trends
- Sensitive topics that may escalate
- Competitive disadvantages
### Phase 4: Report Generation
Generate a complete, self-contained HTML report using the template structure below.
The template is provided inline — no external file dependencies are required.
**File naming**: `{target_name}{days}day_sentiment_report_{YYYYMMDD}.html`
**Report sections**:
1. **Header** — Title, monitoring period, generation date
2. **KPI Overview** — Overall sentiment score (0-100), positive/neutral/negative ratios, event count, active platforms
3. **Sentiment Distribution** — Visual bar chart and trend description
4. **Event Timeline** — Chronological list with sentiment and impact tags
5. **Platform Performance** — Cross-platform activity comparison
6. **Risk Assessment Matrix** — Current risks with severity and recommendations
7. **Operational Recommendations** — Short-term (1-2 weeks), mid-term (1 month), long-term (3+ months)
8. **Disclaimer** — Data source clarification
### Phase 5: Delivery
1. Save the HTML report using the Write tool
2. Display the report preview using preview_url (if available)
3. Deliver the file using deliver_attachments (if available)
4. If tools are unavailable, provide the file path for manual access
## Guidelines
- All data must originate from public web sources — fabrication is strictly prohibited
- Unavailable data must be clearly marked as "Data Unavailable"
- Time ranges are calculated automatically based on the current date
- Sentiment analysis should be evidence-based, avoiding subjective assumptions
- Reports should maintain objectivity, presenting multiple viewpoints for controversial events
- Sensitive political content should be avoided in reports
## Report Template
Use the following HTML structure as the report template. All CSS is embedded inline — no external stylesheets, fonts, or scripts are required. Replace `{PLACEHOLDER}` tokens with actual data.
```html
<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>{TITLE}</title>
<style>
* { margin: 0; padding: 0; box-sizing: border-box; }
body {
font-family: -apple-system, "PingFang SC", "Microsoft YaHei", sans-serif;
background: #f5f7fa; color: #1a1a2e; line-height: 1.6; padding: 20px;
}
.report {
max-width: 900px; margin: 0 auto; background: #fff;
border-radius: 12px; box-shadow: 0 2px 20px rgba(0,0,0,0.08); overflow: hidden;
}
.report-header {
background: linear-gradient(135deg, #1a1a2e, #16213e); color: #fff;
padding: 40px 30px; text-align: center;
}
.report-header h1 { font-size: 28px; margin-bottom: 12px; }
.report-header .meta { font-size: 14px; opacity: 0.8; }
.report-header .meta span { margin: 0 12px; }
.kpi-section { padding: 30px; }
.kpi-grid {
display: grid; grid-template-columns: repeat(auto-fit, minmax(180px, 1fr));
gap: 16px; margin-bottom: 24px;
}
.kpi-card {
background: linear-gradient(135deg, #f8f9fa, #e9ecef); border-radius: 10px;
padding: 20px; text-align: center; border-left: 4px solid #0f3460;
}
.kpi-card .value { font-size: 32px; font-weight: 700; color: #0f3460; }
.kpi-card .label { font-size: 13px; color: #666; margin-top: 6px; }
.kpi-card.positive { border-left-color: #27ae60; }
.kpi-card.positive .value { color: #27ae60; }
.kpi-card.negative { border-left-color: #e74c3c; }
.kpi-card.negative .value { color: #e74c3c; }
.kpi-card.neutral { border-left-color: #f39c12; }
.kpi-card.neutral .value { color: #f39c12; }
.section { padding: 0 30px 30px; }
.section-title {
font-size: 20px; font-weight: 600; color: #1a1a2e; margin-bottom: 20px;
padding-bottom: 10px; border-bottom: 2px solid #e9ecef;
display: flex; align-items: center; gap: 10px;
}
.section-title .icon { font-size: 22px; }
.sentiment-bar {
display: flex; height: 36px; border-radius: 8px; overflow: hidden; margin-bottom: 16px;
}
.sentiment-bar .positive { background: #27ae60; }
.sentiment-bar .neutral { background: #f39c12; }
.sentiment-bar .negative { background: #e74c3c; }
.sentiment-legend { display: flex; gap: 24px; font-size: 14px; color: #555; }
.sentiment-legend span { display: flex; align-items: center; gap: 6px; }
.sentiment-legend .dot {
width: 12px; height: 12px; border-radius: 50%; display: inline-block;
}
.timeline { position: relative; padding-left: 30px; }
.timeline::before {
content: ''; position: absolute; left: 8px; top: 0; bottom: 0;
width: 2px; background: #e0e0e0;
}
.timeline-item { position: relative; margin-bottom: 24px; }
.timeline-item::before {
content: ''; position: absolute; left: -26px; top: 6px;
width: 12px; height: 12px; border-radius: 50%;
background: #0f3460; border: 2px solid #fff; box-shadow: 0 0 0 2px #0f3460;
}
.timeline-item.positive::before { background: #27ae60; box-shadow: 0 0 0 2px #27ae60; }
.timeline-item.negative::before { background: #e74c3c; box-shadow: 0 0 0 2px #e74c3c; }
.timeline-item .date { font-size: 13px; color: #999; margin-bottom: 4px; }
.timeline-item .title { font-size: 16px; font-weight: 600; margin-bottom: 6px; }
.timeline-item .desc { font-size: 14px; color: #555; }
.timeline-item .tag {
display: inline-block; font-size: 12px; padding: 2px 8px;
border-radius: 4px; margin-top: 6px; color: #fff;
}
.tag.positive { background: #27ae60; }
.tag.neutral { background: #f39c12; }
.tag.negative { background: #e74c3c; }
.tag.impact-high { background: #8e44ad; }
.tag.impact-mid { background: #2980b9; }
.tag.impact-low { background: #95a5a6; }
.risk-table { width: 100%; border-collapse: collapse; font-size: 14px; }
.risk-table th {
background: #1a1a2e; color: #fff; padding: 12px 16px; text-align: left;
}
.risk-table td { padding: 12px 16px; border-bottom: 1px solid #eee; }
.risk-table tr:hover { background: #f8f9fa; }
.risk-badge {
display: inline-block; padding: 2px 10px; border-radius: 12px;
font-size: 12px; font-weight: 600; color: #fff;
}
.risk-badge.high { background: #e74c3c; }
.risk-badge.mid { background: #f39c12; }
.risk-badge.low { background: #27ae60; }
.advice-block { margin-bottom: 20px; }
.advice-block h4 {
font-size: 16px; color: #0f3460; margin-bottom: 10px;
padding-left: 12px; border-left: 3px solid #0f3460;
}
.advice-block ul { list-style: none; padding: 0; }
.advice-block ul li {
padding: 8px 0 8px 20px; position: relative; font-size: 14px; color: #444;
}
.advice-block ul li::before {
content: '>'; position: absolute; left: 0; color: #0f3460; font-weight: 700;
}
.disclaimer {
background: #f8f9fa; padding: 20px 30px; font-size: 12px;
color: #999; border-top: 1px solid #eee;
}
@media (max-width: 600px) {
body { padding: 10px; }
.report-header { padding: 24px 20px; }
.report-header h1 { font-size: 22px; }
.kpi-grid { grid-template-columns: repeat(2, 1fr); }
.section, .kpi-section { padding: 20px; }
}
</style>
</head>
<body>
<div class="report">
<div class="report-header">
<h1>{TITLE}</h1>
<div class="meta">
<span>{PERIOD}</span>
<span>{DATE}</span>
</div>
</div>
<div class="kpi-section">
<div class="kpi-grid">
<div class="kpi-card positive">
<div class="value">{POSITIVE}%</div>
<div class="label">Positive</div>
</div>
<div class="kpi-card neutral">
<div class="value">{NEUTRAL}%</div>
<div class="label">Neutral</div>
</div>
<div class="kpi-card negative">
<div class="value">{NEGATIVE}%</div>
<div class="label">Negative</div>
</div>
<div class="kpi-card">
<div class="value">{HOT_COUNT}</div>
<div class="label">Key Events</div>
</div>
</div>
</div>
<div class="section">
<div class="section-title"><span class="icon">📊</span> Sentiment Distribution</div>
<div class="sentiment-bar">
<div class="positive" style="width: {POSITIVE_NUM}%"></div>
<div class="neutral" style="width: {NEUTRAL_NUM}%"></div>
<div class="negative" style="width: {NEGATIVE_NUM}%"></div>
</div>
<div class="sentiment-legend">
<span><span class="dot" style="background:#27ae60"></span> Positive {POSITIVE}%</span>
<span><span class="dot" style="background:#f39c12"></span> Neutral {NEUTRAL}%</span>
<span><span class="dot" style="background:#e74c3c"></span> Negative {NEGATIVE}%</span>
</div>
<p style="margin-top:16px; color:#555; font-size:14px;">{TREND_SUMMARY}</p>
</div>
<div class="section">
<div class="section-title"><span class="icon">📅</span> Key Events Timeline</div>
<div class="timeline">
<div class="timeline-item {EVENT_CLASS}">
<div class="date">{EVENT_DATE}</div>
<div class="title">{EVENT_TITLE}</div>
<div class="desc">{EVENT_DESC}</div>
<span class="tag {EVENT_CLASS}">{EVENT_SENTIMENT}</span>
<span class="tag impact-{EVENT_IMPACT}">{EVENT_IMPACT_LABEL}</span>
</div>
</div>
</div>
<div class="section">
<div class="section-title"><span class="icon">📰</span> Platform Performance</div>
</div>
<div class="section">
<div class="section-title"><span class="icon">⚠</span> Risk Assessment</div>
<table class="risk-table">
<thead><tr><th>Risk</th><th>Level</th><th>Recommendation</th></tr></thead>
<tbody>
<tr><td>{RISK_DESC}</td><td><span class="risk-badge {RISK_LEVEL}">{RISK_LEVEL_LABEL}</span></td><td>{RISK_SUGGESTION}</td></tr>
</tbody>
</table>
</div>
<div class="section">
<div class="section-title"><span class="icon">💡</span> Recommendations</div>
<div class="advice-block">
<h4>Short-term (1-2 weeks)</h4>
<ul><li>{ADVICE_SHORT_1}</li><li>{ADVICE_SHORT_2}</li></ul>
</div>
<div class="advice-block">
<h4>Mid-term (1 month)</h4>
<ul><li>{ADVICE_MID_1}</li><li>{ADVICE_MID_2}</li></ul>
</div>
<div class="advice-block">
<h4>Long-term (3+ months)</h4>
<ul><li>{ADVICE_LONG_1}</li><li>{ADVICE_LONG_2}</li></ul>
</div>
</div>
<div class="disclaimer">
<p>This report is based on publicly available web information and is for reference only.</p>
<p>Report generated by AI; does not represent any official position.</p>
</div>
</div>
</body>
</html>
```
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