git:20251120.7631801 to git:20251120.3801243

---

name: categorizing-bsky-accounts

description: Analyze and categorize Bluesky accounts by topic using keyword extraction. Use when users mention Bluesky account analysis, following/follower lists, topic discovery, account curation, or network analysis.

---

# Categorizing Bluesky Accounts

Analyze Bluesky accounts and categorize them by topic using keyword extraction from posts and bios. Supports multiple input modes: direct handle lists, following lists, and follower lists.

## Prerequisites

**Requires:** extracting-keywords skill (provides YAKE venv + domain stopwords)

The analyzer delegates keyword extraction to the extracting-keywords skill, which provides:

- Optimized YAKE installation with minimal dependencies

- Domain-specific stopwords: English (574), AI/ML (1357), Life Sciences (1293)

- Support for 34 languages

## Quick Start

The analyzer provides three input modes:

**Direct handle list:**

```bash

```

**Analyze following list:**

```bash

```

**Using AI/ML domain stopwords (recommended for tech-focused accounts):**

```bash

```

**Using Life Sciences stopwords (for biomedical/research accounts):**

```bash

```

**Analyze followers:**

```bash

```

**From file:**

```bash

```

## Core Workflow

When users request Bluesky account analysis:

1. **Determine input mode** based on user's request:

- List of handles → use `--handles`

- "Following list" → use `--following`

- "Followers" → use `--followers`

- File provided → use `--file`

2. **Configure analysis parameters:**

- `--accounts N` - Number to analyze (default: 10, max: 100)

- `--posts N` - Posts per account (default: 20, max: 100)

- `--filter "Category1,Category2"` - Only analyze matching categories

- `--exclude "pattern1,pattern2"` - Skip accounts with matching keywords

3. **Run analysis:**

```bash

```

4. **Choose output format:**

- Grouped view (default): Accounts organized by topic

- Detailed view (`--detailed`): Full keyword analysis per account

- JSON export (`--format json`): Structured data

- CSV export (`--format csv`): Spreadsheet-compatible

- Markdown (`--format markdown`): Documentation-ready

## Parameters

### Input Modes (choose one)

**--handles "h1,h2,h3"**

Comma-separated list of Bluesky handles

**--following HANDLE**

Analyze accounts followed by HANDLE

**--followers HANDLE**

Analyze accounts following HANDLE

**--file PATH**

Read handles from file (one per line)

### Analysis Options

**--accounts N**

Number of accounts to analyze (1-100, default: 10)

**--posts N**

Posts to fetch per account (1-100, default: 20)

**--filter "Cat1,Cat2"**

Only analyze accounts matching these categories

**--exclude "word1,word2"**

Skip accounts with these keywords in bio/posts

**--stopwords [en|ai|ls]**

Stopwords to use for keyword extraction (default: en)

- `en`: English stopwords (574 terms) - general purpose

- `ai`: AI/ML domain stopwords (1357 terms) - tech-focused accounts

- `ls`: Life Sciences stopwords (1293 terms) - biomedical/research accounts

**--categories PATH**

Custom category definitions (JSON file)

### Output Options

**--format [grouped|detailed|json|csv|markdown]**

Output format (default: grouped)

**--output PATH**

Output file path (default: /home/claude/bluesky_analysis.json)

**--confidence**

Show categorization confidence scores

## Category Customization

Create custom category definitions in JSON:

```json

{

"AI/ML": {

"keywords": ["ai", "llm", "machine learning", "model", "neural"],

"weight": 1.0

},

"Web3": {

"keywords": ["blockchain", "crypto", "web3", "defi", "dao"],

"weight": 1.0

},

"Science": {

"keywords": ["research", "paper", "phd", "university", "study"],

"weight": 1.0

}

}

```

Use custom categories:

```bash

```

### Default Categories

The analyzer includes these default categories:

- **AI/ML**: Artificial intelligence, machine learning, LLMs

- **Software Dev**: Programming, coding, development tools

- **Philosophy**: Philosophical discourse, consciousness, ethics

- **Music**: Music creation, streaming, artists

- **Law/Policy**: Legal, copyright, policy, regulation

- **Engineering**: Infrastructure, systems, architecture

- **Science**: Research, academia, scientific work

- **Other**: Accounts that don't fit defined categories

## Common Workflows

### Audit Your Following List

Discover topic distribution in accounts you follow:

```bash

```

### Find Experts in a Topic

Filter by category to find ML researchers in someone's network:

```bash

```

### Categorize a List

Analyze a curated list of accounts:

```bash

cat > accounts.txt << 'EOF'

expert1.bsky.social

expert2.bsky.social

expert3.bsky.social

EOF

```

### Export for Further Analysis

Generate structured data for processing:

```bash

```

### Filter Out Bot Accounts

Skip accounts matching spam patterns:

```bash

```

## Output Formats

### Grouped View (Default)

Accounts organized by detected category:

```

## AI/ML (5 accounts)

**John Smith** (@john.bsky.social)

AI researcher focusing on LLM alignment

Topics: alignment, safety, ai research, interpretability

**Jane Doe** (@jane.bsky.social)

Building ML infrastructure at Scale Co

Topics: mlops, kubernetes, infrastructure, deployment

```

### Detailed View

Full keyword analysis for each account:

```

John Smith (@john.bsky.social)

Posts analyzed: 20

Bio: AI researcher focusing on LLM alignment

Top Keywords:

• alignment (0.0234)

• safety research (0.0287)

• interpretability (0.0312)

```

### JSON Format

Structured data for programmatic use:

```json

{

"accounts": [

{

"handle": "john.bsky.social",

"display_name": "John Smith",

"category": "AI/ML",

"confidence": 0.85,

"keywords": [

{"keyword": "alignment", "score": 0.0234},

{"keyword": "safety research", "score": 0.0287}

]

}

]

}

```

### CSV Format

Spreadsheet-compatible output:

```csv

handle,display_name,category,confidence,top_keywords

john.bsky.social,John Smith,AI/ML,0.85,"alignment, safety research, interpretability"

```

## Advanced Usage

### Pagination for Large Lists

For following lists >100 accounts:

```bash

# First batch

# Use cursor from batch1 for next batch (automatically handled internally)

```

### Confidence Scoring

Show how strongly accounts match categories:

```bash

```

Output includes confidence scores:

- 0.9-1.0: Very strong match

- 0.7-0.9: Strong match

- 0.5-0.7: Moderate match

- <0.5: Weak match (may be miscategorized)

### Combining Filters

Analyze specific subset with multiple criteria:

```bash

--filter "AI/ML,Science" \

--exclude "crypto,nft" \

--accounts 50 \

--posts 30

```

## Technical Details

### Keyword Extraction

Delegates to **extracting-keywords skill** using YAKE venv:

- **Stopwords options** (--stopwords):

- `en`: English (574 terms) - general purpose

- `ai`: AI/ML domain (1357 terms) - filters technical noise, ML boilerplate

- `ls`: Life Sciences (1293 terms) - filters research methodology, clinical terms

- N-grams: 1-3 words

- Deduplication: 0.9 threshold

- Top keywords: 15 per account

- Performance: ~5% overhead with domain stopwords vs English

### API Rate Limits

Bluesky API limits:

- 3000 requests per 5 minutes

- 5000 requests per hour

The analyzer respects these limits with built-in delays.

### Categorization Algorithm

1. Extract keywords from recent posts (default: 20)

2. Combine with bio/description text

3. Match against category patterns

4. Score each category by keyword overlap

5. Assign highest-scoring category

6. Calculate confidence based on score distribution

### Data Privacy

The analyzer:

- Only accesses public profile data

- Does not store credentials

- Operates read-only

- Respects Bluesky's terms of service

## Troubleshooting

**"No accounts to analyze"**

- Verify handle format (include domain: handle.bsky.social)

- Check if account exists and has public following/followers

**"Insufficient content for keyword extraction"**

- Account has few posts (<5)

- Posts are very short

- Try increasing `--posts` parameter

**Rate limit errors**

- Reduce `--accounts` parameter

- Add delays between batches

- Check Bluesky API status

**Import errors**

- Verify extracting-keywords skill is available

- Check YAKE venv exists: `/home/claude/yake-venv/bin/python -c "import yake"`

- Verify Python 3.8+: `python3 --version`

## Integration with Other Skills

**Built-in integration:**

- **extracting-keywords**: Automatically delegates keyword extraction to this skill's optimized YAKE venv with domain-specific stopwords

## Example Sessions

**User:** "Can you analyze the accounts I follow on Bluesky and tell me what topics they focus on?"

**Claude:**

```python

# Run analyzer on user's following list

```

**User:** "Find ML researchers in @alice's network and export to CSV"

**Claude:**

```python

--filter "AI/ML,Science" \

--format csv \

--output ml_researchers.csv

```

**User:** "Here's a list of 30 accounts, categorize them with custom topics"

**Claude:**

```python

# First, save custom categories

cat > my_categories.json << 'EOF'

{

"Climate Tech": {

"keywords": ["climate", "sustainability", "clean energy", "carbon"],

"weight": 1.0

},

"Biotech": {

"keywords": ["biotech", "crispr", "genomics", "protein"],

"weight": 1.0

}

}

EOF

# Then analyze with custom categories

```