Categorizing Bsky Accounts

Categorizing Bluesky Accounts

Fetch Bluesky account data and extract keywords for Claude to categorize by topic. The script compresses account context (bio + posts) into bio + keywords, then Claude performs intelligent categorization.

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

Core Workflow

When users request Bluesky account analysis:

• Ensure keyword extraction is set up - Invoke the extracting-keywords skill using the Skill tool to ensure YAKE venv exists (skip if already invoked in this session)

• Determine input mode based on user's request:
• Following list → use --following handle
• Followers → use --followers handle
• List of handles → use --handles "h1,h2,h3"
• File provided → use --file accounts.txt

• Configure parameters:
• --accounts N - Number to analyze (default: 100, max: 100)
• --posts N - Posts per account (default: 20, max: 100)
• --stopwords [en|ai|ls] - Choose domain-specific stopwords:
• en: English (general purpose)
• ai: AI/ML domain (recommended for tech accounts)
• ls: Life Sciences (for biomedical/research accounts)
• --exclude "pattern1,pattern2" - Skip spam/bot accounts

• Run script - Outputs simple text format to stdout:

   @handle1.bsky.social (Display Name)
   Bio text here
   Keywords: keyword1, keyword2, keyword3

   @handle2.bsky.social (Another Name)
   Bio text here
   Keywords: keyword4, keyword5, keyword6

• Categorize accounts - Claude analyzes bio + keywords to categorize by topic

Quick Start

Analyze following list with AI/ML stopwords:

python scripts/bluesky_analyzer.py --following austegard.com --stopwords ai

Analyze followers:

python scripts/bluesky_analyzer.py --followers austegard.com

Analyze specific handles:

python scripts/bluesky_analyzer.py --handles "user1.bsky.social,user2.bsky.social,user3.bsky.social"

From file:

python scripts/bluesky_analyzer.py --file accounts.txt --stopwords ai

Filter out bot accounts:

python scripts/bluesky_analyzer.py --following handle --exclude "bot,spam,promo" --stopwords ai

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: 100)

--posts N

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

--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

--exclude "word1,word2"

Skip accounts with these keywords in bio/posts

Output Format

The script outputs simple text format for Claude to process:

@alice.bsky.social (Alice Smith)
AI researcher working on LLM alignment and safety
Keywords: alignment, safety research, interpretability, llm evaluation

@bob.bsky.social (Bob Johnson)
Full-stack developer building web applications
Keywords: react, typescript, node.js, api design, postgresql

@carol.bsky.social (Carol Williams)
Biotech researcher studying CRISPR applications
Keywords: crispr, gene editing, therapeutics, clinical trials

Claude then categorizes accounts based on bio + keywords without hardcoded rules.

Common Workflows

Audit Your Following List

python scripts/bluesky_analyzer.py --following your-handle.bsky.social --stopwords ai

Claude will categorize accounts by topic and identify patterns in who you follow.

Find Experts in a Topic

python scripts/bluesky_analyzer.py --following alice.bsky.social --stopwords ai

Ask Claude: "Which of these accounts are ML researchers?" or "Who focuses on climate tech?"

Analyze a Curated List

cat > accounts.txt << 'EOF'
expert1.bsky.social
expert2.bsky.social
expert3.bsky.social
EOF

python scripts/bluesky_analyzer.py --file accounts.txt --stopwords ls

Filter Out Bot Accounts

python scripts/bluesky_analyzer.py --following handle --exclude "bot,spam,promo,follow back" --stopwords ai

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: 10 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

Script's role:

• Fetch account data (bio + posts)
• Extract keywords to compress context
• Output bio + keywords in simple format

Claude's role:

• Read bio + keywords for each account
• Intelligently categorize by topic (no hardcoded rules)
• Group accounts, identify patterns, answer user questions

This agentic pattern is more flexible than hardcoded keyword matching.

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 scripts/bluesky_analyzer.py --following user-handle.bsky.social --stopwords ai

Based on the output, I can see you follow:

• AI/ML researchers (15 accounts): Focus on LLM safety, alignment, interpretability
• Software engineers (20 accounts): Web development, React, TypeScript, DevOps
• Writers (8 accounts): Tech journalism, newsletters, long-form content
• Scientists (7 accounts): Climate science, biotech, physics

User: "Find ML researchers in @alice's network"

Claude:

python scripts/bluesky_analyzer.py --following alice.bsky.social --stopwords ai

I found 23 ML researchers in Alice's network:

• 8 working on LLM alignment and safety
• 6 focused on model evaluation and benchmarks
• 5 in ML infrastructure and MLOps
• 4 in computer vision and multimodal models

User: "Here's a list of 30 accounts, categorize them"

Claude:

python scripts/bluesky_analyzer.py --file accounts.txt --stopwords ai

Categorized into:

• Climate Tech (8 accounts)
• Biotech (6 accounts)
• Fintech (5 accounts)
• AI/ML (7 accounts)
• Other (4 accounts)