agentrepocoach

v0.4.0 suspicious
5.0
Medium Risk

Score your codebase on how ready it is for AI agents — and coach you through the fixes.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows some concerning signs, particularly with its use of potentially dangerous functions that could lead to code injection or execution. However, there are no clear indications of malicious intent or active credential harvesting.

  • High obfuscation risk due to use of 'os.system', 'exec(', 'eval(', and '__import__'
  • Low metadata activity and new maintainer increase suspicion
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access.
  • Shell: The shell execution appears to be related to command-line argument handling, possibly for displaying help text, which is generally benign.
  • Obfuscation: The presence of obfuscation patterns such as 'os.system', 'exec(', 'eval(', and '__import__' suggests potential for code injection or execution, indicating a higher risk.
  • Credentials: No clear signs of credential harvesting detected.
  • Metadata: Low activity and new maintainer suggest potential risk, but no clear malicious indicators.

📦 Package Quality Overall: Medium (6.2/10)

✦ High Test Suite 9.0

Test suite present — 11 test file(s) found

  • Test runner config found: pyproject.toml
  • 11 test file(s) detected (e.g. test_quality.py)
✦ High Documentation 9.0

Well-documented package

  • Documentation URL: "Documentation" -> https://WouterDeBot.github.io/agentrepocoach
  • Detailed PyPI description (7843 chars)
  • Classifier: Documentation
○ 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

  • 257 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 25 commits in WouterDeBot/agentrepocoach
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • os.system", "exec(", "eval(", "__import__", ) def test_bootstrap_signals_has_no_f
⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

  • s listed.""" result = subprocess.run( [sys.executable, "-m", "agentrepocoach", "--hel
  • elp text.""" result = subprocess.run( [sys.executable, "-m", "agentrepocoach", "--hel
✓ 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 score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "WouterDeBot" 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 agentrepocoach 
Create a Python-based mini-application called 'AI-Agent-Ready-Assistant' which leverages the 'agentrepocoach' package to assess and enhance the readiness of a given codebase for integration with AI agents. This tool should serve as both an evaluator and a guide, helping developers understand the current state of their projects in terms of AI compatibility and suggesting actionable steps for improvement.

The application should perform the following core functions:
1. Accept input from the user to specify the directory of the codebase they want to evaluate.
2. Use 'agentrepocoach' to analyze the codebase, scoring it based on predefined criteria relevant to AI-agent integration.
3. Provide a detailed report highlighting strengths and weaknesses of the codebase concerning AI-agent compatibility.
4. Offer specific recommendations and coaching tips to help improve the score.
5. Allow users to track progress over time by saving results and comparing them against previous assessments.

Additionally, consider implementing these optional features to enrich the application:
- A user-friendly graphical interface to visualize the assessment scores and trends over time.
- Integration with popular version control systems like Git to automatically check the status of codebases at different commit points.
- An option for users to submit their codebases for remote evaluation if they prefer not to install the 'agentrepocoach' package locally.

Your task is to design and implement this application, ensuring it provides value to software developers looking to future-proof their projects for AI-driven workflows.