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categorizing-bsky-accountsBsky 帐户分类

Agent Skill

categorizing-bsky-accounts 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

734

周安装

30

GitHub Stars

118

下载量

238
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:categorizing-bsky-accounts(Bsky 帐户分类)
来源仓库:https://github.com/oaustegard/claude-skills
仓库路径:skills/categorizing-bsky-accounts
安装命令:
npx skills add https://github.com/oaustegard/claude-skills --skill categorizing-bsky-accounts
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/oaustegard/claude-skills --skill categorizing-bsky-accounts

简介

categorizing-bsky-accounts 从 Bluesky 账户资料与动态中提取关键词,并由 Claude 完成主题分类,形成结构化标签体系。

  • 适用于舆情分析、社群洞察或内容运营场景,帮助识别不同领域的活跃用户与话题焦点。
  • 依赖 extracting-keywords 技能提供的 YAKE 关键词引擎与领域停用词库,需提前安装并配置环境。
  • 输入为 Bluesky 用户名或帖子链接,输出为压缩后的关键词向量与分类结果,便于后续批量处理。
  • 注意隐私边界,仅处理公开数据,不得用于追踪个人或抓取敏感信息,遵守平台速率限制与使用条款。

SKILL.md

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

  1. 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

  1. 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
  2. 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

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)

适合场景

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用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

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能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.67%
按下载量换算87

Claude

30.21%
按下载量换算72

Cursor

19.38%
按下载量换算46

Gemini CLI

10.92%
按下载量换算26

安全审计

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Snyk

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权限和风险

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安装前确认

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