Sentiment Tracker

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 history

Quick Reference

TopicFileSetup processsetup.mdMemory templatememory-template.md

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

EndpointData SentPurposeSearch engines (via web_search)Query textFind mentionsSocial platforms (via web_fetch)URL requestsRead 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 data branding — brand strategy and guidelines monitor — system and service monitoring

Feedback

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