- name
- Sentiment Tracker
- slug
- sentiment-tracker
- version
- 1.0.0
- homepage
- https://clawic.com/skills/sentiment-tracker
- description
- Monitor brand sentiment, crypto opinions, and product perception across social media with automated tracking, alerts, and multi-entity dashboards.
- metadata
- {"clawdbot":{"emoji":"📊","requires":{"bins":[]},"os":["linux","darwin","win32"]}}
Sentiment Analysis
Track what people say about anything — brands, crypto, products, competitors — across Twitter/X, Reddit, YouTube, Hacker News, and news sites.
One-shot analysis for quick checks. Scheduled monitoring for ongoing tracking. Multi-entity dashboards to compare multiple things at once.
Setup
On first use, read setup.md and follow its guidelines. Data is stored locally in ~/sentiment-analysis/.
When to Use
User wants to know public opinion about something. Could be:
- "What are people saying about [brand]?"
- "How's sentiment on [crypto] right now?"
- "Monitor [product] mentions and alert me on negative spikes"
- "Compare sentiment: [brand A] vs [brand B]"
Architecture
Data lives in ~/sentiment-analysis/. See memory-template.md for setup.
~/sentiment-analysis/
├── memory.md # Config, entities, preferences
├── entities/ # One file per tracked entity
│ ├── brand-name.md
│ └── crypto-xyz.md
├── reports/ # Generated analysis reports
│ └── YYYY-MM-DD-entity.md
└── alerts.md # Alert historyQuick Reference
| Topic | File |
|---|---|
| Setup process | setup.md |
| Memory template | memory-template.md |
Core Rules
1. Source Diversity Matters
Never rely on a single platform. Each source has bias:
- Twitter/X: Real-time, emotional, viral content
- Reddit: Longer discussions, honest opinions, niche communities
- YouTube: Comments show product experiences
- Hacker News: Tech-focused, skeptical, early adopter views
- News sites: Official narratives, PR-filtered
Use at least 2-3 sources per analysis. Note source distribution in reports.
2. Time Windows Change Everything
Sentiment shifts fast. Always specify and report time window:
- Last 24h: Breaking news, viral events
- Last 7d: Weekly trends, sustained campaigns
- Last 30d: Product launches, seasonal patterns
Default: Last 7 days unless user specifies otherwise.
3. Quantify, Don't Guess
Every report includes concrete metrics:
📊 Entity: [Name]
🕐 Period: [Date range]
📈 Volume: [X mentions found]
😊 Positive: XX% | 😠 Negative: XX% | 😐 Neutral: XX%
Top Themes:
1. [Theme] — XX mentions, XX% negative
2. [Theme] — XX mentions, XX% positive
Notable Posts:
- [Quote] — [Platform, engagement]4. Alerts Are Specific
Don't alert on every change. Track baselines and alert on:
- Negative spike >20% above baseline
- Viral negative post (>10x normal engagement)
- New negative theme appearing
- Competitor positive spike
5. Multi-Entity Comparison
When tracking multiple entities, always show relative performance:
📊 Sentiment Comparison (Last 7d)
| Entity | Volume | Positive | Negative | Trend |
|--------|--------|----------|----------|-------|
| Brand A | 1,240 | 62% | 18% | ↗️ +5% |
| Brand B | 890 | 45% | 32% | ↘️ -8% |6. Scheduled Monitoring
For ongoing tracking, use cron. Default schedules:
- Critical entities: Daily at 09:00
- Regular entities: Every 3 days
- Background entities: Weekly
Store schedule in memory.md. Deliver reports to user's preferred channel.
7. Save Everything
After each analysis:
- Update entity file with new data
- Compare to previous analysis
- Note trend changes
- Archive raw findings
Common Traps
- Single-source analysis → Completely skewed view. Reddit hates everything, Twitter loves drama. Always cross-reference.
- No time window → "Sentiment is positive" means nothing without dates. A product can be loved one week, hated the next.
- Vanity metrics → High volume ≠ positive sentiment. 1000 mentions with 80% negative is worse than 100 mentions with 60% positive.
- Ignoring context → A spike in "crypto X is dead" might be sarcasm or memes. Read actual posts, not just keyword counts.
- Alert fatigue → Alerting on every fluctuation makes users ignore alerts. Only signal meaningful changes.
External Endpoints
| Endpoint | Data Sent | Purpose |
|---|---|---|
| Search engines (via web_search) | Query text | Find mentions |
| Social platforms (via web_fetch) | URL requests | Read content |
No API keys required. No data stored externally. All analysis happens locally.
Security & Privacy
Data that leaves your machine:
- Search queries sent to web search (query text only)
- URL requests to public posts (reading only)
Data that stays local:
- All entity tracking in ~/sentiment-analysis/
- Historical sentiment data
- Alert configurations
This skill does NOT:
- Require accounts on any platform
- Store data on external servers
- Send personal information anywhere
- Access private/protected content
Related Skills
Install with clawhub install <slug> if user confirms:
analytics— web traffic and conversion databranding— brand strategy and guidelinesmonitor— system and service monitoring
Feedback
- If useful:
clawhub star sentiment-tracker - Stay updated:
clawhub sync