🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators, with no network or shell execution risks. However, the metadata suggests low maintainer effort and community engagement, raising some concern.

Low network and shell execution risks
Potential concerns due to low maintainer effort and community presence

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
Shell: No shell execution detected, reducing the risk of potential command injection attacks.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of low maintainer effort and lack of community presence, which may indicate potential risks.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with agent-shell-py

Create a Python-based mini-application called 'AgentRunner' that leverages the 'agent-shell-py' package to manage and execute various command-line interface (CLI) agents headlessly. This application will serve as a versatile tool for developers and system administrators who need to automate tasks using different CLI tools without the need for manual intervention.

Step-by-Step Guide:
1. Define the core functionality of 'AgentRunner', which includes discovering available CLI agents, scheduling their execution at specific intervals, and logging the output/results of each run.
2. Implement a user-friendly interface where users can input commands, specify schedules, and view logs directly within the application.
3. Utilize 'agent-shell-py' to abstract away the complexities of interacting with different CLI tools, ensuring seamless execution of agents regardless of their underlying implementation details.
4. Add advanced features such as error handling, retry mechanisms for failed executions, and notifications upon completion or failure of tasks.
5. Ensure that 'AgentRunner' supports multiple execution environments (e.g., local, cloud), allowing it to be deployed flexibly across different setups.
6. Incorporate a configuration file mechanism to store user preferences, agent configurations, and schedule information persistently.
7. Develop comprehensive documentation and examples to guide new users on how to integrate and use 'AgentRunner' effectively.

Suggested Features:
- Support for both synchronous and asynchronous agent execution.
- Integration with popular scheduling libraries (like APScheduler) to handle recurring tasks.
- Real-time monitoring and control over running agents.
- Ability to pause, resume, or terminate ongoing agent processes from the UI.
- Detailed logging with customizable log levels (info, warning, error).
- Extensibility through plugins or modules for adding support for new CLI agents.
- Compatibility with containerization technologies like Docker for consistent execution environments.

How 'agent-shell-py' is Utilized:
- Use 'agent-shell-py' to encapsulate the logic for executing CLI commands, handling input/output streams, and managing subprocesses efficiently.
- Leverage its capabilities to streamline the interaction between 'AgentRunner' and the CLI agents, ensuring robustness and ease of use.
- Rely on 'agent-shell-py' to provide a clean API for scheduling and controlling agent runs, facilitating the development of a more sophisticated automation tool.