Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
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Passive domain reconnaissance using Python stdlib. Subdomain discovery, SSL certificate inspection, WHOIS lookups, DNS records, domain availability checks, and bulk multi-domain analysis. No API keys required.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Passive domain reconnaissance using only Python stdlib. Zero dependencies. Zero API keys. Works on Linux, macOS, and Windows.
This skill includes scripts/domain_intel.py — a complete CLI tool for all domain intelligence operations.
# Subdomain discovery via Certificate Transparency logs
python3 SKILL_DIR/scripts/domain_intel.py subdomains example.com
# SSL certificate inspection (expiry, cipher, SANs, issuer)
python3 SKILL_DIR/scripts/domain_intel.py ssl example.com
# WHOIS lookup (registrar, dates, name servers — 100+ TLDs)
python3 SKILL_DIR/scripts/domain_intel.py whois example.com
# DNS records (A, AAAA, MX, NS, TXT, CNAME)
python3 SKILL_DIR/scripts/domain_intel.py dns example.com
# Domain availability check (passive: DNS + WHOIS + SSL signals)
python3 SKILL_DIR/scripts/domain_intel.py available coolstartup.io
# Bulk analysis — multiple domains, multiple checks in parallel
python3 SKILL_DIR/scripts/domain_intel.py bulk example.com github.com google.com
python3 SKILL_DIR/scripts/domain_intel.py bulk example.com github.com --checks ssl,dns
SKILL_DIR is the directory containing this SKILL.md file. All output is structured JSON.
| Command | What it does | Data source |
|---|---|---|
subdomains | Find subdomains from certificate logs | crt.sh (HTTPS) |
ssl | Inspect TLS certificate details | Direct TCP:443 to target |
whois | Registration info, registrar, dates | WHOIS servers (TCP:43) |
dns | A, AAAA, MX, NS, TXT, CNAME records | System DNS + Google DoH |
available | Check if domain is registered | DNS + WHOIS + SSL signals |
bulk | Run multiple checks on multiple domains | All of the above |
web_search for general research about what a domain/company doesweb_extract to get the actual content of a webpageterminal with curl -I for a simple "is this URL reachable" check| Task | Better tool | Why |
|---|---|---|
| "What does example.com do?" | web_extract | Gets page content, not DNS/WHOIS data |
| "Find info about a company" | web_search | General research, not domain-specific |
| "Is this website safe?" | web_search | Reputation checks need web context |
| "Check if a URL is reachable" | terminal with curl -I | Simple HTTP check |
| "Find subdomains of X" | This skill | Only passive source for this |
| "When does the SSL cert expire?" | This skill | Built-in tools can't inspect TLS |
| "Who registered this domain?" | This skill | WHOIS data not in web search |
| "Is coolstartup.io available?" | This skill | Passive availability via DNS+WHOIS+SSL |
Pure Python stdlib (socket, ssl, urllib, json, concurrent.futures).
Works identically on Linux, macOS, and Windows with no dependencies.
All queries are passive — no port scanning, no vulnerability testing:
Contributed by @FurkanL0
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Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
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Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
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Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.
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Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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