Agent skill

ping

Enhanced ping command with visual data representations like heatmaps and bar charts. Core Scenario: When the user needs to monitor network reachability with visual metrics.

Stars 19
Forks 4

Install this agent skill to your Project

npx add-skill https://github.com/x-cmd/skill/tree/main/data/x-cmd/ping

SKILL.md

ping - Enhanced Network Reachability

The ping module provides an enhanced interface for the standard connectivity test, supporting multiple visualization modes to better understand network performance and latency.

When to Activate

  • When checking if a remote host is reachable via ICMP.
  • When needing a visual representation (heatmap, bar chart) of network latency over time.
  • When exporting reachability data to CSV or TSV for analysis.

Core Principles & Rules

  • Visualization: Use --heatmap or --bar for immediate visual feedback on latency stability.
  • Data-Friendly: Supports structured output formats for integration with monitoring tools.

Patterns & Examples

Visual Monitoring

bash
# Ping a host and display a real-time heatmap of latency
x ping --heatmap bing.com

Data Export

bash
# Ping a host 10 times and output results as CSV
x ping -c 10 --csv 8.8.8.8

Checklist

  • Confirm the target host address.
  • Verify if a specific visualization mode is requested.

Expand your agent's capabilities with these related and highly-rated skills.

x-cmd/skill

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.

19 4
Explore
x-cmd/skill

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.

19 4
Explore
x-cmd/skill

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.

19 4
Explore
x-cmd/skill

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.

19 4
Explore
x-cmd/skill

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.

19 4
Explore
x-cmd/skill

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.

19 4
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results