Trend Monitor

Discover what the data science community is talking about right now.

When to Use This Skill

Use on a regular cadence:

•Daily: Quick scan for breaking news and viral discussions
•Weekly: Deep scan for emerging trends and content opportunities
•Ad-hoc: When planning content calendar or looking for inspiration

Sources to Monitor

Primary Sources (Data Science Focus)

Source	Type	Signal
Reddit	Community	What practitioners are struggling with
r/datascience	Discussion	Career, tools, techniques
r/Python	Technical	Libraries, updates, tutorials
r/MachineLearning	Research	Papers, breakthroughs, debates
r/dataengineering	Infrastructure	Pipelines, tools, architecture
Hacker News	Tech news	What's getting attention
Show HN	Launches	New tools and projects
Ask HN	Questions	Common problems
X/Twitter	Real-time	What influencers are discussing
Data science accounts	Opinions	Hot takes, debates
Tool announcements	News	New releases
GitHub Trending	Code	What developers are building
Python repos	Libraries	Emerging tools
Data repos	Datasets	New resources

Secondary Sources

Source	Type	Best For
arXiv	Research	Cutting-edge papers
cs.LG, stat.ML	ML papers	New techniques
Dev.to / Medium	Tutorials	What people are learning
Data science tags	Articles	Tutorial gaps
YouTube	Video	Popular explanations
Data channels	Tutorials	What's getting views
Newsletters	Curated	What curators find important
Data Elixir, TLDR	Aggregators	Pre-filtered content

LATAM-Specific Sources

Source	Language	Focus
Twitter LATAM	Spanish	Regional discussions
Data science en español	Spanish	Community conversations
Reddit en español	Spanish	r/programacion, r/cienciadedatos
YouTube español	Spanish	Tutorial demand

Monitoring Process

Step 1: Source Scan

For each source, look for:

code

SIGNALS TO TRACK:
├── 🔥 High engagement (upvotes, comments, shares)
├── 📈 Rapid growth (trending, viral)
├── ❓ Unanswered questions (content gaps)
├── 🆕 New releases (tools, libraries, updates)
├── 💬 Active debates (controversial topics)
└── 🇲🇽 LATAM relevance (Spanish content needs)

Step 2: Relevance Filtering

Score each finding against tacosdedatos criteria:

Criterion	Weight	Questions
Audience fit	30%	Would our readers care?
Timeliness	25%	Is this happening now?
Unique angle	20%	Can we add value others aren't?
Expertise match	15%	Can we speak authentically?
Content pillar	10%	Does it fit our categories?

Step 3: Pitch Generation

For top candidates, generate pitch summaries:

markdown

## Trend: [Topic Name]

**Source**: [Where discovered]
**Signal strength**: 🔥🔥🔥 (1-5 fires)
**Timeliness**: [Breaking / This week / Emerging]

**What's happening**:
[2-3 sentence summary]

**Why it matters for our audience**:
[Connection to tacosdedatos readers]

**Potential angles**:
1. [Angle 1 - e.g., tutorial]
2. [Angle 2 - e.g., opinion piece]
3. [Angle 3 - e.g., comparison]

**Competition check**:
- [Existing content on this topic]
- [Our differentiation opportunity]

**Recommended action**: [Write now / Queue for next week / Monitor]

Output Format

Daily Scan Output

markdown

# Trend Monitor: [Date]

## 🔥 Hot Right Now (Act Today)

### 1. [Trend Name]
- **Source**: [Reddit/HN/Twitter]
- **Signal**: [X upvotes / X comments / trending]
- **Quick take**: [One sentence]
- **Action**: [Suggested response]

### 2. [Trend Name]
...

## 📈 Building Momentum (This Week)

### 1. [Trend Name]
...

## 👀 Worth Watching (Monitor)

- [Topic 1]: [Why watching]
- [Topic 2]: [Why watching]

## 📊 Source Stats

| Source | Items Scanned | Relevant | Hot |
|--------|---------------|----------|-----|
| Reddit | X | X | X |
| HN | X | X | X |
| Twitter | X | X | X |

Weekly Deep Scan Output

markdown

# Weekly Trend Report: [Week of Date]

## Executive Summary

**Top opportunity**: [Best content idea this week]
**Emerging theme**: [Pattern across sources]
**Community mood**: [What people are feeling]

## Pitch Candidates (Ranked)

### 🥇 Priority 1: [Topic]
[Full pitch summary - see template above]

### 🥈 Priority 2: [Topic]
[Full pitch summary]

### 🥉 Priority 3: [Topic]
[Full pitch summary]

## Trend Analysis

### What's Rising
- [Trend 1]: [Why it's growing]
- [Trend 2]: [Why it's growing]

### What's Fading
- [Topic 1]: [Why declining interest]
- [Topic 2]: [Why declining interest]

### Evergreen Opportunities
- [Topic that's always relevant]
- [Topic that's always relevant]

## LATAM-Specific Insights

### Spanish Content Gaps
- [Topic with no good Spanish coverage]
- [Topic with no good Spanish coverage]

### Regional Trends
- [LATAM-specific trend]
- [Mexico-specific trend]

## Recommended Content Calendar

| Day | Topic | Type | Why Now |
|-----|-------|------|---------|
| Mon | [Topic] | Tutorial | [Reason] |
| Wed | [Topic] | Opinion | [Reason] |
| Fri | [Topic] | Roundup | [Reason] |

## Sources Summary

### Most Active This Week
1. [Source]: [Key discussion]
2. [Source]: [Key discussion]

### New Sources Discovered
- [New blog/newsletter/account to follow]

Search Queries

Reddit Searches

code

# r/datascience
site:reddit.com/r/datascience [topic] after:2024-01-01
sort:top time:week

# Cross-subreddit
(site:reddit.com/r/datascience OR site:reddit.com/r/Python) [topic]

Hacker News Searches

code

# Via Algolia HN Search
https://hn.algolia.com/?q=[topic]&type=story&dateRange=pastWeek&sort=byPopularity

# Show HN launches
https://hn.algolia.com/?q=show%20hn%20[topic]&type=story

Twitter/X Searches

code

# Trending in data science
(data science OR machine learning OR python) min_faves:100 lang:en
(ciencia de datos OR aprendizaje automático) min_faves:50 lang:es

# From specific accounts
from:@account [topic]

GitHub Trending

code

# Trending Python repos
https://github.com/trending/python?since=weekly

# Topic-specific
https://github.com/topics/[topic]?o=desc&s=stars

Automation Ideas

Daily Automated Checks

yaml

# Potential automation (for future MCP integration)
schedule: "0 6 * * *"  # 6 AM daily

sources:
  reddit:
    subreddits: [datascience, Python, MachineLearning]
    sort: hot
    limit: 25

  hackernews:
    type: topstories
    limit: 30
    filter: [data, python, ml, ai]

  twitter:
    lists: [data-science-influencers]
    min_engagement: 100

output:
  format: markdown
  destination: daily-trends.md
  notify: true

Integration with Pipeline

Trend Monitor feeds into the content pipeline:

code

trend-monitor
    ↓
[Pitch candidates]
    ↓
tacosdedatos-pipeline (Phase 1: Ideation)
    ↓
[Human selects from candidates]
    ↓
[Content production begins]

Quality Checklist

Before reporting a trend:

• Verified across multiple sources?
• Not just one viral post?
• Relevant to tacosdedatos audience?
• We can add unique value?
• Timing makes sense?
• Not already covered recently?

Anti-Patterns

Mistake	Problem	Solution
Chasing every trend	Exhaustion, off-brand content	Filter ruthlessly
Ignoring LATAM	Missing core audience	Always check Spanish sources
Only English sources	Incomplete picture	Balance with Spanish content
Reacting too slow	Trend already peaked	Daily monitoring, quick response
No unique angle	"Me too" content	Always find differentiation

Related Skills

•tacosdedatos-pipeline — Full content production
•beat-reporter agent — Research and drafting
•content-to-social — Distribution after creation