Agent skill
route
Display the system's network routing table with support for structured data export. Core Scenario: When the user needs to inspect the routing table for network path diagnostics.
Install this agent skill to your Project
npx add-skill https://github.com/x-cmd/skill/tree/main/data/x-cmd/route
SKILL.md
route - Network Routing Table Viewer
The route module provides an interface to view the system's network routing table, allowing users to inspect how network traffic is directed. It supports exporting the table in structured formats.
When to Activate
- When diagnosing network reachability or routing issues.
- When needing a structured list (CSV) of the current routing table for analysis.
Core Principles & Rules
- Experimental Status: Be aware that this module is currently in an experimental phase.
- Data Export: Supports
--csvfor easy parsing.
Patterns & Examples
View Routing Table
# Display the current routing table
x route
Export to CSV
# Output the routing table as a CSV
x route --csv
Checklist
- Confirm if the user needs a general view or a structured export.
- Verify the system environment as routing table formats may vary.
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?