🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks due to low maintainer activity and poor metadata quality, despite showing no direct malicious intent or shell execution.

Low maintainer activity and poor metadata quality suggest potential abandonment or lack of updates.
No significant network or shell execution risks identified.

Per-check LLM notes

Network: The observed network calls are likely legitimate for downloading resources and managing configurations, but could be monitored for unusual behavior.
Shell: No shell execution patterns detected, suggesting low risk of direct system command execution.
Metadata: The package shows signs of low maintainer activity and poor metadata quality, which could indicate potential risk.

📦 Package Quality Overall: Low (3.0/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

Test runner config found: pyproject.toml

○ Low Documentation 1.0

No documentation detected

No documentation URL, doc files, or meaningful description found

○ Low Contributing Guide 2.0

No contributing guide or governance files found

No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found

◈ Medium Type Annotations 5.0

Partial type annotation coverage

224 type-annotated function signatures detected in source

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

config self.session = requests.Session() headers = dict(config.headers) user_agent
try: response = requests.get(download_url, timeout=_DOWNLOAD_TIMEOUT, stream=True)
raise response = requests.get(public_url, timeout=_DOWNLOAD_TIMEOUT, stream=True)

✓ 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 ap-client

Your task is to create a command-line utility called 'AgentControl' using the Python package 'ap-client'. This tool will allow users to manage agents on an Agent Platform through its API. Your application should be user-friendly and provide robust functionalities to interact with the platform efficiently. Here’s a detailed breakdown of what your application should achieve:

1. **User Authentication**: Implement a login feature where users can authenticate themselves using their credentials provided by the Agent Platform. Use the 'ap-client' package to handle the authentication process seamlessly.
2. **Agent Management**: Provide commands to list all available agents, start or stop specific agents, and retrieve detailed information about any agent. Utilize the 'ap-client' package to communicate with the Agent Platform API for these operations.
3. **Configuration Management**: Allow users to update configuration settings for individual agents. Users should be able to specify which agent they want to modify and what settings need updating. Again, leverage the 'ap-client' package for interfacing with the API.
4. **Logs Retrieval**: Enable users to fetch logs from any agent. This feature should support specifying the time range and log level for more targeted log retrieval.
5. **Health Checks**: Integrate a functionality to perform health checks on agents. This includes checking if an agent is running smoothly and retrieving any associated alerts or warnings.
6. **Documentation and Help**: Ensure your utility has comprehensive documentation and a help command that explains each feature and provides usage examples.

To achieve these functionalities, you will heavily rely on the 'ap-client' package. It offers a client library and command-line interface for interacting with the Agent Platform API. Make sure to explore the official documentation of 'ap-client' to understand its methods and how best to utilize them in your application.