🎁 Get the FREE AI Skills Starter Guide β€” Subscribe β†’
BytesAgainBytesAgain
πŸ¦€ ClawHub

Sentiment Tracker

by @ivangdavila

Monitor brand sentiment, crypto opinions, and product perception across social media with automated tracking, alerts, and multi-entity dashboards.

Versionv1.0.0
Downloads1,099
Installs3
Stars⭐ 2
TERMINAL
clawhub install sentiment-tracker

πŸ“– About This Skill


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":"πŸ“Š","requires":{"bins":[]},"os":["linux","darwin","win32"]}}

Sentiment Analysis

Track what people say about anything β€” brands, crypto, products, competitors β€” 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/
    β”œβ”€β”€ memory.md           # Config, entities, preferences
    β”œβ”€β”€ entities/           # One file per tracked entity
    β”‚   β”œβ”€β”€ brand-name.md
    β”‚   └── crypto-xyz.md
    β”œβ”€β”€ reports/            # Generated analysis reports
    β”‚   └── YYYY-MM-DD-entity.md
    └── alerts.md           # Alert history
    

    Quick 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:
    πŸ“Š Entity: [Name]
    πŸ• Period: [Date range]
    πŸ“ˆ Volume: [X mentions found]
    😊 Positive: XX% | 😠 Negative: XX% | 😐 Neutral: XX%

    Top Themes: 1. [Theme] β€” XX mentions, XX% negative 2. [Theme] β€” XX mentions, XX% positive

    Notable Posts:

  • [Quote] β€” [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:
    πŸ“Š Sentiment Comparison (Last 7d)

    | Entity | Volume | Positive | Negative | Trend | |--------|--------|----------|----------|-------| | Brand A | 1,240 | 62% | 18% | ↗️ +5% | | Brand B | 890 | 45% | 32% | β†˜οΈ -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: 1. Update entity file with new data 2. Compare to previous analysis 3. Note trend changes 4. Archive raw findings

    Common Traps

  • Single-source analysis β†’ Completely skewed view. Reddit hates everything, Twitter loves drama. Always cross-reference.
  • No time window β†’ "Sentiment is positive" means nothing without dates. A product can be loved one week, hated the next.
  • Vanity metrics β†’ High volume β‰  positive sentiment. 1000 mentions with 80% negative is worse than 100 mentions with 60% positive.
  • Ignoring context β†’ A spike in "crypto X is dead" might be sarcasm or memes. Read actual posts, not just keyword counts.
  • Alert fatigue β†’ 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 if user confirms:
  • analytics β€” web traffic and conversion data
  • branding β€” brand strategy and guidelines
  • monitor β€” system and service monitoring
  • Feedback

  • If useful: clawhub star sentiment-tracker
  • Stay updated: clawhub sync
  • ⚑ When to Use

    TriggerAction
    - "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]"

    βš™οΈ Configuration

    On first use, read setup.md and follow its guidelines. Data is stored locally in ~/sentiment-analysis/.