AI Analysis
The package has a moderate risk score due to potential misuse of network calls and concerns over the maintainer's activity level and repository engagement.
- Network risk present
- Inactive maintainer/new maintainer
- Low community engagement
Per-check LLM notes
- Network: The presence of network calls is expected if the package interacts with external services, but should be reviewed to ensure it aligns with the package's intended functionality.
- Shell: No shell execution patterns were detected.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package maintainer is new or inactive, and the repository lacks community engagement, raising some suspicion but not definitive evidence of malice.
Package Quality Overall: Low (3.8/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (3786 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
49 type-annotated function signatures detected in source
Limited contributor diversity
2 unique contributor(s) across 19 commits in Labic-ICMC-USP/Agents4GovAppsTwo distinct contributors found
Heuristic Checks
Found 1 network call pattern(s)
try: response = requests.get(base_url, params=params, timeout=10) response.ra
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
1 maintainer concern(s) found
Author "LABIC - ICMC/USP" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a mini-application called 'PublicInfoBot' that serves as an intelligent assistant for citizens of Brazil seeking information about public services and government policies. This application will utilize the 'agents4gov-apps' Python package to provide a seamless interaction between users and the Brazilian government's digital platforms. Here are the steps and features to implement: 1. **Setup Environment**: Install Python and the 'agents4gov-apps' package in your development environment. 2. **User Interface**: Develop a simple command-line interface (CLI) or a basic web interface where users can input their queries related to public services such as healthcare, education, and social benefits. 3. **Query Processing**: Use the 'agents4gov-apps' package to process user inputs. The package should handle natural language understanding, allowing the bot to interpret the intent behind the userβs query. 4. **Data Retrieval**: Integrate with official Brazilian government APIs or databases through the 'agents4gov-apps' package to fetch accurate and up-to-date information on public services and policies. 5. **Response Generation**: Based on the retrieved data, generate human-readable responses that are concise yet informative. Ensure the responses are tailored to the specific needs expressed in the userβs query. 6. **Feedback Loop**: Implement a mechanism for users to rate the accuracy and helpfulness of the responses provided by PublicInfoBot. This feedback will be used to improve the bot's performance over time. 7. **Security Measures**: Ensure all interactions are secure and comply with Brazilian data protection laws, using the security features provided by the 'agents4gov-apps' package. 8. **Documentation**: Provide clear documentation on how to install, run, and contribute to PublicInfoBot, including examples of how to extend its capabilities with new features or integrations. By following these steps and utilizing the 'agents4gov-apps' package, you will create a valuable tool for Brazilian citizens to easily access important information about public services and government policies.