Agent skill

codex

Enhanced CLI for OpenAI's Codex terminal agent, supporting local code analysis, sandboxing, and third-party models. Core Scenario: When the user wants to use Codex with specific models (DeepSeek, etc.), enable sandboxed execution, or run natural language commands.

View SKILL.md on GitHub Repository
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/codex

SKILL.md

codex - AI Code Assistant & Terminal Agent

The codex module enhances OpenAI's codex terminal agent, enabling semantic code search, automated patch generation, and connection to various AI model providers within a secure, sandboxed environment.

When to Activate

  • When the user wants to start a Codex session with a specific provider (e.g., DeepSeek, Kimi, Zhipu, Doubao, SiliconFlow).
  • When the user needs to execute shell commands or generate code based on natural language descriptions.
  • When the user requires a sandboxed execution environment (read-only, workspace-write) for safety.
  • When the user wants to apply generated diffs to their Git worktree.
  • When the user needs to inject specific "skills" into the Codex agent's environment.

Core Principles & Rules

  • Sandboxing: Always encourage using appropriate sandbox strategies (--sandbox) to prevent unintended system changes.
  • Automation Levels: Use --full-auto for a balance between speed and safety (approves on failure).
  • Provider Switching: Use subcommands like ds (DeepSeek), kimi, zhipu, doubao, or sili (SiliconFlow) to launch Codex with these providers.
  • Non-Interactive Execution: Use exec or e for quick, one-off commands or code generation tasks.

Additional Scenarios

  • Web Search: Enable real-time web search capabilities using the --search flag for up-to-date information.
  • Git Integration: Quickly apply the latest generated diff from the agent using x codex apply.
  • Local OSS Models: Connect to local Ollama services by using the --oss flag.

Patterns & Examples

Run Natural Language Command

bash
# Execute a command described in English
x codex e "List all files larger than 10MB in the current directory"

Start with Third-party Providers

bash
# Launch Codex using DeepSeek with read-only sandbox protection
x codex ds --sandbox read-only

# Launch Codex using SiliconFlow
x codex sili

Apply Latest Patch

bash
# Apply the latest generated code patch to the current Git repository
x codex apply

Inject Skills

bash
# Manage and inject custom skills into the Codex agent environment
x codex skill

Checklist

  • Confirm the desired sandbox level (read-only, workspace-write, etc.).
  • Verify if a specific model provider (DeepSeek, Kimi, etc.) is needed.
  • Ensure the user is aware of the risks when using dangerously-bypass-approvals-and-sandbox.

Recommended Agent Skills

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