Agent skill
free
Display memory usage with support for CSV/TSV formats and cross-platform (Linux/macOS) compatibility. Core Scenario: When the user needs to monitor RAM usage, buffer/cache, or export memory data for automation.
Install this agent skill to your Project
npx add-skill https://github.com/x-cmd/skill/tree/main/data/x-cmd/free
SKILL.md
free - Memory Usage Reporting
The free module enhances the standard memory reporting tool by adding structured data support (CSV/TSV) and providing a native implementation for macOS users who typically lack the free command.
When to Activate
- When monitoring total, used, and free system memory.
- When performing memory usage analysis in scripts using CSV/TSV formats.
- When checking memory compression details on macOS.
- When needing periodic memory reporting (polling).
Core Principles & Rules
- Cross-Platform: Provides a consistent interface for memory stats on both Linux and macOS.
- Automation-Ready: Supports
--csvand--tsvfor easy parsing without headers. - Real-Time Polling: Use
-sand-cto repeat the output at intervals.
Patterns & Examples
Human-Readable View
# Display system memory usage in a clear format
x free
Export for Scripting
# Get memory data as a single-line CSV without headers
x free --csv --no-header
Periodic Monitoring
# Refresh memory stats every 2 seconds for 10 iterations
x free -s 2 -c 10
Checklist
- Verify if the output needs to be structured (CSV/TSV) for a script.
- Confirm if headers should be included or omitted.
- Ensure the correct polling interval is set if monitoring over time.
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?