AI-powered insights for developer profiles.
Built by Kasata, ResumeRadar AI parses public GitHub repositories to extract programming languages, detects underlying frameworks from README documentation, and evaluates project health signals through a production-grade FastAPI engine.
Deterministic & Verifiable: Skills are counted by occurrences across repository languages and README heuristics.
Engineered for Ground Truth, Not Fluff
Every feature in ResumeRadar AI is rooted directly in the open-source repository. No hallucinated resumes, no black-box scoring.
GitHub Profile Analysis
Fetches public repositories asynchronously via the GitHub REST API. Inspects repository metadata, commit recency, primary programming languages, and default branches with full rate-limit handling.
Repository & Technology Detection
Combines the GitHub Languages API with regex-based keyword detection in README files to discover underlying technologies like FastAPI, React, Docker, Redis, TensorFlow, and PostgreSQL.
Developer Project Insights
Evaluates project health across 6 concrete criteria: README availability, non-empty description, updates within 365 days, multi-language usage, topic tags, and external project links.
Optional LinkedIn Profile Input
Accepts optional LinkedIn URLs to parse structured role and certification data. Built with an extensible schema that seamlessly bridges public snapshots with official LinkedIn OAuth APIs.
AI-Assisted Analysis
Transforms fragmented Git repositories into an aggregated developer tech stack profile. Synthesizes technology frequencies and quality indicators without black-box hallucinations.
Realistic Profile Analysis in Action
Explore the exact data model, quality criteria, and skill detection metrics generated by the ResumeRadar AI engine.
ResumeRadar_AI
A production-ready FastAPI backend for analyzing GitHub profiles and LinkedIn profiles to extract skills, technologies, and project quality.
distributed-task-orchestrator
Lightweight async event consumer and worker dispatch engine built with Redis streams and Python asyncio.
cloud-metrics-dashboard
Fullstack telemetry observation deck featuring real-time latency heatmaps and server health monitors.
postgres-query-analyzer
Automated slow-query profiling tool that checks EXPLAIN ANALYZE plans and indexes.
How ResumeRadar AI Operates
Four simple steps from raw developer links to deep, actionable technical insights.
Enter GitHub Profile
Provide any public GitHub username or URL. ResumeRadar AI validates the handle format and prepares async requests to the GitHub REST API.
Add LinkedIn Optionally
Attach a LinkedIn profile identifier to extract role records and certifications alongside code artifacts, using standard schema models.
Analyze Developer Profile
FastAPI orchestrates parallel queries: interrogating the GitHub Languages API, scanning README markdown for 18+ frameworks, and testing 6 quality benchmarks.
Explore Generated Insights
Consume clean, structured JSON detailing skill occurrence frequencies, strong project classifications, and comprehensive developer profile health.
A Native REST API for Profiling Automation
ResumeRadar AI operates as a serverless REST API on Netlify. Embed profile intelligence directly into internal hiring workflows, developer dashboards, portfolio builders, or vetting pipelines.
GITHUB_TOKEN to elevate limits from 60 to 5,000 requests/hour.curl -X POST /api/analyze \
-H "Content-Type: application/json" \
-d '{
"github_url": "https://github.com/Kasa1905",
"linkedin_url": "https://linkedin.com/in/kaushiksambe"
}'100% Open Source. Community Driven.
ResumeRadar AI is licensed under the permissive MIT License. Inspect the source code, run the 41 automated pytest test suites, fork the repository, or deploy your own private profiling instance without vendor lock-in.
About Kasata
The technology venture creating transparent developer tooling.
Kasata is a specialized developer tools venture focused on automated code analysis engines, developer profile intelligence, and open-source infrastructure.
Our flagship open-source release, ResumeRadar AI, was founded on a simple principle: developer evaluation should be deterministic, verifiable, and free of synthetic inflation. Rather than predicting unverified skills or relying on buzzwords, ResumeRadar AI inspects public Git commits, repository languages, and documentation signals to present an authentic picture of developer capability.
Operating at kasata.me, we believe in the power of open-source software, transparent algorithms, and developer-first APIs that can be independently audited and integrated without friction.
Verifiable Data
Every detected skill links to verifiable repositories and public markdown documentation.
Open Source
MIT licensed architecture with public test suites, transparent roadmap, and community contributions.
Developer First
Built by developers for developers, with clean REST APIs and modular Pydantic data schemas.
Contact Kasata
Have questions about ResumeRadar AI, custom integrations, or partnerships? Reach our team directly at kasata@kasta.me.
Kasata Headquarters
Official inquiries, developer integration support, and open-source collaboration.
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