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Categorizing Bsky Accounts skill

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.

$npx skills add oaustegard/claude-skills --skill categorizing-bsky-accounts
View this skill on GitHuboaustegard/claude-skills/categorizing-bsky-accounts/SKILL.md
Pack stars
257
Pack installs
3.7k
Alyn Score
55/99
Updated
8 h ago
License
MIT
– views – installs via Alyn

oaustegard

Categorizing Bsky Accounts

Install Categorizing Bsky Accounts

Pick your agent. Every command is ready to paste.

$npx skills add oaustegard/claude-skills --skill categorizing-bsky-accounts

The open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.

01

Install it

Run the command above, or upload the folder in Claude.

02

Ask naturally

Describe the task. Your agent loads categorizing-bsky-accounts when the request matches its description.

03

Name it if needed

If it does not trigger, say “use the categorizing-bsky-accounts skill”. In Codex, type $categorizing-bsky-accounts.

The skill itself

SKILL.md

FolderGitHub

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:

  1. 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)

  2. 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
  3. 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
  4. 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
    
  5. 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:

  1. Fetch account data (bio + posts)
  2. Extract keywords to compress context
  3. Output bio + keywords in simple format

Claude's role:

  1. Read bio + keywords for each account
  2. Intelligently categorize by topic (no hardcoded rules)
  3. 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

Categorizing Output

Group accounts by topic from their bio + keywords, using judgment rather than a fixed taxonomy — the categories and counts follow from what's actually in the data, not a template.

Tips for Categorizing Bsky Accounts

  • • Start a fresh session after installing so your agent picks up the new skill.
  • • This skill ships scripts. Read them before the first run, and run it in a project without secrets first.
  • • It is part of a pack with 30 skills. Install only the ones you need with --skill to keep triggers precise.
  • • If two skills overlap, mention the one you want by name.

Questions about Categorizing Bsky Accounts

What does the Categorizing Bsky Accounts skill do?

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.

How do I install Categorizing Bsky Accounts?

Run "npx skills add oaustegard/claude-skills --skill categorizing-bsky-accounts" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.

Does Categorizing Bsky Accounts work in Cursor and Codex?

Yes. Categorizing Bsky Accounts uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.

Is Categorizing Bsky Accounts free?

Categorizing Bsky Accounts is open source on GitHub under the MIT license. It is free to install; check the license before commercial use.

Who made Categorizing Bsky Accounts?

Categorizing Bsky Accounts is published by oaustegard in the oaustegard/claude-skills repository, together with 29 other skills.

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