AI Analysis
The package shows minimal risk indicators with no network calls, shell executions, or obfuscations. The main concern lies in the unavailability of the repository and the maintainer's limited history, but these alone do not conclusively indicate malicious intent.
- No network calls detected.
- No shell execution detected.
- Repository and maintainer have limited visibility.
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution detected, indicating no immediate risk of command injection or similar attacks.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
- Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
- Metadata: The repository is not found and the maintainer has limited history, raising concerns but not definitive proof of malice.
Package Quality Overall: Low (4.6/10)
Partial test coverage signals detected
1 test file(s) detected (e.g. test_counter.py)
Some documentation present
Documentation URL: "Documentation" -> https://github.com/luciddreamer/ai-token-counter#readmeDetailed PyPI description (3124 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
21 type-annotated function signatures detected in source
Could not retrieve contributor data from GitHub
GitHub API error: 404
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: luciddreamer.dev>
All external links appear legitimate
Repository not found (deleted or private)
Repository not found (deleted or private)
2 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor "LucidDreamer" 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 command-line utility named 'TokenTally' that leverages the Python package 'ai-token-counter' to provide users with a straightforward way to count tokens across various large language models (LLMs). This tool should accept user input as text or read from a file, and then display the token count according to different LLMs such as GPT-3, Claude, and others supported by the 'ai-token-counter' package. Step 1: Install the required packages including 'ai-token-counter'. Step 2: Design a clean and intuitive command-line interface that allows users to specify the input source (stdin or file) and the target LLM. Step 3: Implement functionality to accurately count tokens based on the selected LLM using the 'ai-token-counter' package. Step 4: Enhance the utility with additional features such as: - Displaying the total character count alongside the token count. - Providing an option to estimate costs based on the token count, considering typical pricing models of the LLM providers. - Offering a summary of the most common words or phrases in the input text. Step 5: Ensure the application handles errors gracefully, providing meaningful feedback to the user when issues arise. Your task is to develop this utility from scratch, ensuring it is well-documented and easy to use. The 'ai-token-counter' package should be utilized to demonstrate its capabilities in handling different LLM tokenization schemes.