Agent skill
gram
Forcefully terminate all AI agent processes, archive their memory data, and clean up source files. **DANGEROUS**: This is a "kill-switch" tool. AI agents should ONLY use this if they identify an out-of-control situation or if the user explicitly requests a complete AI shutdown. Core Scenario: When the user needs to stop runaway or malfunctioning AI agents and reset their state or clean up memory.
Install this agent skill to your Project
npx add-skill https://github.com/x-cmd/skill/tree/main/data/x-cmd/gram
SKILL.md
gram - AI Termination & Memory Cleanup (DANGEROUS)
The gram module is a safety tool designed to forcefully terminate AI-related processes and manage their memory data in case of unexpected or dangerous behavior.
[!CAUTION] DANGEROUS OPERATION: This tool will kill processes and delete data. It is meant as a "kill-switch". AI agents should proceed with extreme caution and always confirm with the user before using high safety levels (3-5).
When to Activate
- When the user reports that an AI agent is malfunctioning or out of control.
- When the user needs to free up system resources occupied by AI processes.
- When the user wants to securely archive and remove AI memory/soul files.
- When there's a need to "sever" all HTTP/HTTPS connections to prevent unauthorized data uploads.
Core Principles & Rules
- Safety Levels (0-5): Use appropriate levels based on the severity of the situation.
0: SIGKILL basic processes (x-cmd, curl).1: Include runtimes (python, nodejs, bun, deno).2: +Sever all HTTP/HTTPS network connections (Recommended Default for safety).3: +Archive and delete folders containingsoul.mdandmemory.mdin $HOME.4: +Kill processes using those memory folders.5: +Expand search to the entire root (/) directory.
- Archive Before Cleanup: Always prefer commands that archive (
tar) data before deletion to allow for later analysis. - Confirmation: AI agents MUST notify the user before executing
x gram stop.
Additional Scenarios
- Emergency Stop: Instantly sever all AI-related network connections to prevent data leaks.
- System Reset: Clean up all local traces of previous AI sessions (memory, souls) to start fresh.
Patterns & Examples
Standard Stop (Level 2)
# Terminate processes and sever network connections
x gram stop 2
Thorough Cleanup (Level 4)
# Terminate processes, sever network, and archive/delete memory folders
x gram stop 4
Archive Specific Memory Folder
# Package a specific folder and delete the original
x gram trm ./my-agent-memory
Checklist
- Confirm the safety level (0-5) matches the user's intent.
- Ensure the user is aware that active AI processes will be terminated.
- Verify if specific memory folders need to be archived.
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?