LIVE
Google Introduces "Gemini 4 Carbon" as Next Step in Its Model Lineup28/10/26 · Google|DeepMind unveils Genie 4, a new generation of world model27/10/26 · Google DeepMind|Anthropic files IPO prospectus, with risk disclosures taking center stage26/10/26 · Anthropic|Robot policy trained only in simulation matches top real-world systems26/10/26|OpenAI unveils GPT-6.1 Terra, a model built for computer use26/10/26 · OpenAI|Google's AI gives evasive answers about who won the 2020 US election28/10/26 · Google|NVIDIA introduces Nemotron 3.5 Transcribe, a promptable multilingual transcription model28/10/26 · NVIDIA|OpenAI and ServiceNow deepen partnership on enterprise workflows28/10/26 · OpenAI|Failed startups' data finds a second life training AI models28/10/26|Anthropic expands AI for Science program to 20 foundations and research institutions28/10/26 · Anthropic|Anthropic shares early results on using Claude to accelerate drug development27/10/26 · Anthropic|GEPA-Curator: Filtering Failures to Better Train LLM Agents27/10/26|Google Introduces "Gemini 4 Carbon" as Next Step in Its Model Lineup28/10/26 · Google|DeepMind unveils Genie 4, a new generation of world model27/10/26 · Google DeepMind|Anthropic files IPO prospectus, with risk disclosures taking center stage26/10/26 · Anthropic|Robot policy trained only in simulation matches top real-world systems26/10/26|OpenAI unveils GPT-6.1 Terra, a model built for computer use26/10/26 · OpenAI|Google's AI gives evasive answers about who won the 2020 US election28/10/26 · Google|NVIDIA introduces Nemotron 3.5 Transcribe, a promptable multilingual transcription model28/10/26 · NVIDIA|OpenAI and ServiceNow deepen partnership on enterprise workflows28/10/26 · OpenAI|Failed startups' data finds a second life training AI models28/10/26|Anthropic expands AI for Science program to 20 foundations and research institutions28/10/26 · Anthropic|Anthropic shares early results on using Claude to accelerate drug development27/10/26 · Anthropic|GEPA-Curator: Filtering Failures to Better Train LLM Agents27/10/26|
Toolofficial publisher

shell (OpenAI)

Tool : A precise action the AI can call · requires openai-api

Shell hosted in a Debian container, network off by default.

The replacement for local_shell: safer, but still code execution.

Overall score
5.6 /10
Security: serious reservations
Utility
7.0
Reliability
6.0
Security
Serious reservations
Ease
5 min · Technical

Security reflects where data goes, requested permissions and incidents on record at the verification date. It is not a guarantee of zero risk: check the deployment mode and the connections you enable.

What it does, concretely

Some tasks require running real system commands: manipulating files, launching scripts, checking software versions, or processing data. OpenAI's shell tool addresses this need by giving the model access to a full terminal environment, without requiring you to manage the infrastructure yourself.

In practice, the model can execute shell commands either in an OpenAI-hosted container (using the container_auto option) or in a local runtime that you host yourself. Access is available through the Responses API only, not through the Chat Completions API. Network access is disabled by default in hosted containers, which limits data exfiltration risks.

This tool is aimed at developers building agents capable of deterministic processing: calculations, file manipulation, running Python or Node.js scripts, or any task requiring a real terminal environment.

It is not suitable for general public use without technical oversight: executing arbitrary shell commands remains a sensitive operation that requires supervision, allowlists or denylists, and activity logging.

What it offers

  • ·Shell command execution in an OpenAI-hosted container, automatically provisioned via the container_auto option (paid).
  • ·Shell command execution in a local runtime that you host and control yourself.
  • ·Access to a full terminal environment with Python and Node.js available in hosted containers.
  • ·Network disabled by default in hosted containers, with the option to enable it as needed.
  • ·Integration via the Responses API, compatible with multiple languages: JavaScript, Python, Go, Java, Ruby.
  • ·tool_choice parameter to control whether the model uses the tool automatically or only on explicit instruction.
  • ·Access to a /mnt/data directory for file manipulation in hosted containers.

In practice

Price
Paid
Commercial use
Commercial use: yes
Available on
api
Host
openai-api
FR interface
No

Security and data

Rating
Security: serious reservations
Capabilities
readswritesexecutesnetwork
Your data
Data with the vendor
Maintenance
Active

Links and repository checked on 25 October 2026 · added on 1 February 2026

How to install shell (OpenAI)

1. Obtain an OpenAI API key and enable access to the Responses API from your dashboard. 2. Install the official SDK in your language of choice (e.g. npm install openai or pip install openai). 3. Configure your API key via the OPENAI_API_KEY environment variable. 4. In your Responses API call, add a tool of type shell with the container_auto environment for a hosted container, or configure your own local runtime. 5. Set tool_choice to auto to let the model decide when to use the shell. 6. Security note: enable network access only if necessary, implement command allowlists, and log all tool activity.
tools=[{"type":"shell"}]

Official documentation ↗

In the same category

Whole category Code →