AI Analysis
Final verdict: SAFE
The package shows minimal signs of risk with no detected shell execution, obfuscation, or credential harvesting. The network and metadata risks are slightly elevated but do not conclusively indicate malicious activity.
- Moderate network risk
- Incomplete maintainer profile
Per-check LLM notes
- Network: The presence of network calls is not unusual, especially if the package relies on external services for functionality.
- Shell: No shell execution patterns detected, which is normal and indicates no direct system command execution risk.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
- Credentials: No credential harvesting patterns detected, indicating secure handling of secrets and credentials.
- Metadata: The maintainer has an incomplete profile and may be new or inactive, raising some suspicion but not conclusive evidence of malice.
Package Quality Overall: Medium (5.4/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
7.0
Some documentation present
Documentation URL: "Documentation" -> https://doc.agentscope.io/Detailed PyPI description (9456 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Development Status classifier >= Beta
◈ Medium
Type Annotations
5.0
Partial type annotation coverage
184 type-annotated function signatures detected in source
✦ High
Multiple Contributors
10.0
Active multi-contributor project
24 unique contributor(s) across 100 commits in agentscope-ai/agentscopeActive community — 5 or more distinct contributors
Heuristic Checks
Outbound Network Calls
score 1.5
Found 1 network call pattern(s)
try: response = requests.get(url) response.raise_for_status() ret
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
Email domain looks legitimate: alibaba-inc.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository agentscope-ai/agentscope appears legitimate
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with agentscope
Create a fully-functional mini-app called 'AgentSim' that simulates a simple economy using the 'agentscope' package. This app will model an economy with different types of agents such as consumers, producers, and traders. Each type of agent will have distinct behaviors and interactions within the economy. Step 1: Define the Economy Model - Define the structure of the economy including resources, goods, and services. - Establish initial conditions for the simulation such as the number of agents, their initial wealth, and resource availability. Step 2: Implement Agents - Use 'agentscope' to create classes for each type of agent: - Consumers: These agents consume goods and services based on their preferences and available resources. - Producers: These agents produce goods and services using resources and technology. - Traders: These agents buy and sell goods and services between themselves and other agents. - Each agent class should include methods for actions like consuming, producing, and trading. Step 3: Simulate Interactions - Utilize 'agentscope' to simulate interactions between agents over multiple time steps. - Track the economic outcomes such as total production, consumption, and wealth distribution. - Implement feedback mechanisms where agent behaviors can adapt based on past interactions. Step 4: Visualization and Analysis - Integrate a visualization tool to graphically represent the state of the economy over time. - Provide analysis tools to evaluate the impact of different scenarios and policies on the economy. - Allow users to experiment with changes to the economy and observe the effects. Suggested Features: - Adjustable parameters for agent behavior and initial conditions. - Real-time updates of the economy state during simulations. - Export simulation results for further analysis or reporting. - User-friendly interface for setting up and running simulations. How to Utilize 'agentscope': - Leverage 'agentscope's capabilities to manage and coordinate the interactions between different types of agents efficiently. - Use its built-in features to track and analyze the complex dynamics of the simulated economy. - Take advantage of 'agentscope's flexibility to easily modify and extend the simulation model as needed.