Agent skill
shodan
Search the Shodan network database for connected devices, vulnerabilities, and real-time network intelligence. Core Scenario: When the user needs to perform network reconnaissance, search for exposed assets, or audit IPs.
Install this agent skill to your Project
npx add-skill https://github.com/x-cmd/skill/tree/main/data/x-cmd/shodan
SKILL.md
shodan - Shodan Network Search CLI
The shodan module provides a comprehensive CLI for the Shodan search engine, enabling network reconnaissance, vulnerability detection, and monitoring of internet-connected assets.
When to Activate
- When performing reconnaissance on specific IPs or domain names.
- When searching for connected devices with specific vulnerabilities (CVEs) or open ports.
- When monitoring network alerts for specific assets.
- When generating real-time network intelligence summaries via AI integration (
::).
Core Principles & Rules
- API Key Management: Remind users to obtain and initialize their Shodan API key via
init. - Targeted Search: Support for powerful filtering based on facets (ports, protocols, countries).
- Data Export: Can download host information and export to structured formats like CSV.
Patterns & Examples
Scan IPs
# Perform a targeted scan on specific IP addresses and ports
x shodan scan create 8.8.8.8 1.1.1.1=53/dns-udp,443/https
Host Information
# Lookup IP information in the Shodan internet database
x shodan internetdb 8.8.8.8
AI Intelligence
# Use AI to summarize Shodan results for specific queries
x shodan :: "critical vulnerabilities in industrial control systems"
Checklist
- Ensure the Shodan API key is configured.
- Verify the search query or target IP range.
- Confirm if the user needs raw data or a summarized report.
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
pufferlib
High-performance reinforcement learning framework optimized for speed and scale. Use when you need fast parallel training, vectorized environments, multi-agent systems, or integration with game environments (Atari, Procgen, NetHack). Achieves 2-10x speedups over standard implementations. For quick prototyping or standard algorithm implementations with extensive documentation, use stable-baselines3 instead.
fluidsim
Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.
metabolomics-workbench-database
Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.
geniml
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
zinc-database
Access ZINC (230M+ purchasable compounds). Search by ZINC ID/SMILES, similarity searches, 3D-ready structures for docking, analog discovery, for virtual screening and drug discovery.
astropy
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
Didn't find tool you were looking for?