🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risks with no network calls, no signs of credential harvesting, and low obfuscation. The only concern is the potential use of shell commands for Git operations which might not be intended for malicious purposes.

No network calls detected
Shell execution possibly for Git operations
No obfuscation or credential harvesting detected

Per-check LLM notes

Network: No network calls detected.
Shell: Shell execution appears to be related to Git operations, possibly for version control purposes.
Obfuscation: No obfuscation patterns detected, suggesting low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.

📦 Package Quality Overall: Medium (5.2/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

Test runner config found: pyproject.toml

◈ Medium Documentation 5.0

Some documentation present

Brief PyPI description (425 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

241 type-annotated function signatures detected in source

◈ Medium Multiple Contributors 6.0

Limited contributor diversity

2 unique contributor(s) across 100 commits in takumiecd/arctx
Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

e.perf_counter() result = subprocess.run( list(command_tuple), cwd=str(resolved_cwd),
ipped string.""" result = subprocess.run( ["git"] + args, cwd=str(cwd), captu
ed HEAD. """ result = subprocess.run( ["git", "symbolic-ref", "--short", "HEAD"],
try: stat_result = subprocess.run( ["git", "diff", "--shortstat", "HEAD~1", "HEAD"
source_sha] result = subprocess.run( cmd, cwd=str(resolved_repo_path),
not dry_run: result = subprocess.run( ["git", "commit", "-m", message], c

✓ 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

Repository takumiecd/arctx appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Takumi Ishida" 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 arctx

Create a collaborative brainstorming tool using the 'arctx' Python package. This tool will allow multiple users to contribute ideas to a shared topic while maintaining a transparent history of all contributions. Each user's input will be stored as nodes in a Directed Acyclic Graph (DAG), where each node represents an idea and its dependencies on previous ideas. This structure will help track the evolution of thoughts and facilitate parallel collaboration without overwriting existing contributions.

Key Features:
- User registration and login system
- Real-time contribution submission
- Display of the entire DAG graph representing the brainstorming session
- Ability to filter contributions based on user or time
- Export of the brainstorming session as a structured document

Utilization of 'arctx':
- Use 'arctx' to manage the DAG of ideas contributed by users. Each idea will be a node in the graph, and dependencies between ideas will form directed edges.
- Implement functions to add new nodes, retrieve the graph structure, and traverse the graph to display or export the brainstorming session.
- Ensure that the package's capabilities for parallel agent collaboration are leveraged to support real-time contributions from multiple users.