AI Analysis
The package shows signs of low effort and lacks transparency, raising suspicion despite having no detected malicious activities.
- Metadata risk due to low effort and lack of transparency
- No clear description or usage documentation
Per-check LLM notes
- Network: The network call uses HTTP request with authorization header, which is potentially legitimate if the package interacts with an API requiring authentication.
- Shell: No shell execution patterns detected.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows signs of low effort and lack of transparency, which raises some suspicion but does not definitively indicate malice.
Package Quality Overall: Low (2.0/10)
No test suite detected
No test files or test-runner configuration detected
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
17 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
Found 2 network call pattern(s)
url: str) -> dict: req = urllib.request.Request(url, headers={ "Authorization": auth,cation/json", }) with urllib.request.urlopen(req, timeout=60) as resp: return json.loads(
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: cern.ch>
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
4 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Your task is to develop a simple yet powerful command-line tool using Python and the 'atlasdocs-jira' package. This tool will enable users to manage Jira issues directly from their terminal. Your goal is to create an intuitive interface where users can perform basic operations such as creating new issues, updating existing ones, and deleting them. Here are the key functionalities your tool should support: 1. **Issue Creation**: Allow users to specify details like summary, description, priority, and assignee when creating a new issue. 2. **Issue Update**: Provide options to update fields such as status, description, and comments of an existing issue. 3. **Issue Deletion**: Implement functionality to delete issues based on their unique ID. 4. **Issue Search**: Enable searching for issues by various criteria including summary, status, and assignee. 5. **User Management**: Facilitate adding and removing users from projects and issues. 6. **Integration Testing**: Ensure all functions work seamlessly with real Jira instances by setting up integration tests. To achieve these objectives, you'll need to leverage the 'atlasdocs-jira' package which provides essential utilities for integrating with Jira. Your implementation should demonstrate a deep understanding of the package’s capabilities and limitations. Additionally, focus on writing clean, maintainable code and include comprehensive documentation to guide other developers. Remember, the user experience is paramount. Design your CLI tool to be as user-friendly as possible, ensuring that even non-technical users can easily interact with it. Lastly, ensure that your tool supports authentication with Jira through secure methods.
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