Pavithra Lokesh M

@pavithra_lokeshai / mlgithub.com/Pavithra29-eng

Public-work score

25/50

Cross-checks resume claims against public GitHub work. Higher scores mean stronger corroborating evidence.

Technical Depth

5/10

Experience Authenticity

7/10

Public Contribution

1/10

Claim Consistency

4/10

Domain Fit

8/10

Demonstrated capabilities

LLM App Dev60% confidence

The 'Pavithra29-eng/SmartBuddy' and 'Pavithra29-eng/CodeMitra' projects are described as AI chatbots and error explanation tools using LLMs and Generative AI, demonstrating basic LLM application development.

RAG Pipelines60% confidence

The 'Pavithra29-eng/SmartBuddy' project explicitly mentions 'RAG LLMs Ollama KD-Tree HNSW (Hierarchical Navigable Small World)' for its document Q&A functionality, indicating experience with RAG pipelines.

Classical ML60% confidence

The 'Pavithra29-eng/LoanIQ' project utilizes Python with Scikit-Learn and Random Forest to predict loan approval decisions, providing evidence of classical machine learning application.

GitHub activity

Verified stack

TypeScriptHTMLJavaScriptPythonSCSSC++

Key evidence

GitHub account age of 2.1 years is consistent with a student starting studies in 2022.
Total contributions are very low, with 73 commits over 2.1 years, 13% active weeks, and a longest streak of only 3 days.
The GitHub primary tech stack by bytes is TypeScript (41.7%), HTML (17.5%), JavaScript (15.9%), Python (14.5%), and C++ (2.8%).
Pinned repositories include 'Pavithra29-eng/SmartBuddy' (Python), 'Pavithra29-eng/CodeMitra' (Python), 'Pavithra29-eng/LoanIQ' (Python), and 'Pavithra29-eng/PrepPulse' (JavaScript), aligning with claimed projects.
All 7 public non-fork repositories have 0 stars, and there are 0 external OSS PRs or reviews, indicating no external validation or community engagement.

Scored 2 Aug 2026