GitHub repository access in containerized environments using REST API and credential detection. Use when git clone fails, or when accessing private repos/writing files via API.
日本語の概要は準備中です。原文の説明を表示しています。
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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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.
Requires: extracting-keywords skill (provides YAKE venv + domain stopwords)
The analyzer delegates keyword extraction to the extracting-keywords skill, which provides:
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 handle--followers handle--handles "h1,h2,h3"--file accounts.txtConfigure 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 accountsRun 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
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
--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)
--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 purposeai: AI/ML domain stopwords (1357 terms) - tech-focused accountsls: Life Sciences stopwords (1293 terms) - biomedical/research accounts--exclude "word1,word2" Skip accounts with these keywords in bio/posts
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.
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.
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?"
cat > accounts.txt << 'EOF'
expert1.bsky.social
expert2.bsky.social
expert3.bsky.social
EOF
python scripts/bluesky_analyzer.py --file accounts.txt --stopwords ls
python scripts/bluesky_analyzer.py --following handle --exclude "bot,spam,promo,follow back" --stopwords ai
Delegates to extracting-keywords skill using YAKE venv:
en: English (574 terms) - general purposeai: AI/ML domain (1357 terms) - filters technical noise, ML boilerplatels: Life Sciences (1293 terms) - filters research methodology, clinical termsBluesky API limits:
The analyzer respects these limits with built-in delays.
Script's role:
Claude's role:
This agentic pattern is more flexible than hardcoded keyword matching.
"No accounts to analyze"
"Insufficient content for keyword extraction"
--posts parameterRate limit errors
--accounts parameterImport errors
/home/claude/yake-venv/bin/python -c "import yake"python3 --versionBuilt-in integration:
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.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
GitHub repository access in containerized environments using REST API and credential detection. Use when git clone fails, or when accessing private repos/writing files via API.
日本語の概要は準備中です。原文の説明を表示しています。
Decide which model, effort level, and cascade shape each subagent gets, and how to keep improvement loops safe (evaluator-as-selector, stop on regression). Routes on measured cost-per-completed-task rather than per-token price, because a tier's token count varies more by task shape than price varies across tiers. Covers per-model effort semantics, the concision lever, cascade preconditions, context handoff, and watching a subagent fan-out live. Use when choosing a subagent's model or effort, when choosing how to escalate a failed attempt, or when asked which model or effort a task should get. Grounded in a 2026-07 calibration, a 2026-08 coding-cost study, a 2026-09 seeded-bug repair battery, a 2026-10 Haiku 5.5 ladder priced per spawn, and a 2026-10 retry-versus-escalation ladder on 295 SWE-bench Verified tasks; Managed Agents API specifics are operational, not calibrated.
日本語の概要は準備中です。原文の説明を表示しています。
Securely manages API credentials for multiple providers (Anthropic Claude, Google Gemini, GitHub). Use when skills need to access stored API keys for external service invocations.
日本語の概要は準備中です。原文の説明を表示しています。
Guidance for asking clarifying questions when user requests are ambiguous, have multiple valid approaches, or require critical decisions. Use when implementation choices exist that could significantly affect outcomes.
日本語の概要は準備中です。原文の説明を表示しています。
Pre-change blast-radius report for a symbol or file. Walks tree-sitting references, augments with a plain-text scan over non-parsed files (configs, plain docs), and clusters affected sites by feature (`_FEATURES.md`) or top-level package. Use when about to refactor, rename, or delete something in a repo you don't own — "what breaks if I change `validateUser`", "who calls this", "is this safe to remove", "where is this used", "blast radius", "impact analysis". This is the CONVERGENT pre-change risk skill — for "what is this repo?" use exploring-codebases; for "where is X?" use searching-codebases.
日本語の概要は準備中です。原文の説明を表示しています。
Read Bluesky/ATProto without depending on Bluesky's AppView — interactions on a user's posts, thread replies, any repo's records, network-wide backlinks across every lexicon, an account's handle and PDS history, which collections are active network-wide, and layer-by-layer outage diagnosis. Use when bsky.app or the AppView is down or slow, when a Bluesky read returns timeouts or 5xx, when asked who liked/replied/quoted/reposted something, when pulling live Bluesky context cheaply, when reading records straight from a PDS, when asked who references a record or account anywhere on the network, whether an account has changed handle or migrated servers, or which lexicons and non-Bluesky apps are active on atproto. Complements browsing-bluesky, which routes everything through the AppView and fails when it does.
日本語の概要は準備中です。原文の説明を表示しています。