Parallel fleet processing
Up to 100 cloud workers fan your repos out through a durable pipeline — Modal for compute, Inngest for orchestration. A 150-repo portfolio analyzes in minutes, not days.
Know what your code is worth.
Diligence-grade scoring for founders, CTOs, and AI engineers. The public-repo scan runs in your browser. Private GitHub access is temporary, and source is not retained.
- Reports are private by default
- Public scans run in your browser
- Review, metrics, and publishing are separate choices
- 151
- repositories analyzed
- 13.5M
- lines of code mapped
- 549,772
- call-graph edges
- 89,492
- ontology mappings
- 236
- contributors traced
- 396
- API endpoints catalogued
Your code stays yours.
The scoring pipeline was designed so that trusting us is not a prerequisite for using it.
P0
Private by default
Source excluded from saved reports
Choose how analysis runs
Public-repo scoring runs in the browser, and the local CLI keeps analysis on your machine. Private GitHub scoring uses temporary server access for that run and does not retain source code.
Nothing is saved automatically
A saved report contains the repository identity, score, dimensions, and derived metrics. Source, snippets, file contents, and secrets are excluded from the saved report.
Every secondary use is separate
Hypebase expert review, de-identified benchmark contribution, and public leaderboard publishing each require a distinct action and disclose exactly what is included.
The score is the front door. The platform is the factory.
Create an account and the same engine that scored your repo goes to work on all of them.
Automated improvers that open PRs
Five scored dimensions, each with a production improver that writes the fix and opens the pull request: docs to 90%, tests to 55%, complexity to 75%, domain diversity to 75%, types to 60%.
Security & CVE scanning
Secrets detection, dependency CVE checks, and a security-pattern graph across every repo — findings ranked by call-graph reach, not just file location.
Due-diligence reports
Investor-grade DD per repo and per portfolio: LOC, test coverage, dependency pinning, CI posture, external service coupling — the table an acquirer's tech DD team builds, pre-built.
Code graph intelligence
Functions, classes, call graphs, and inheritance in a queryable graph database, mapped to the FIBO financial ontology and searchable with hybrid code embeddings.
Value estimation & agentic API discoveryRoadmap
Identify the functions worth productizing, estimate what your codebase could command, and package capabilities as agentic API offerings.
| Dimension | Target | Improver |
|---|---|---|
| Documentation coverage | 90% | Docstring generator with 4-stage verification |
| Test density | 55% | Test stub generator with mutation-informed refinement |
| Complexity | 75% | Complexity refactorer |
| Domain diversity | 75% | Domain classifier |
| Type coverage | 60% | Type annotation generator |
Built on published research, cited in full.
29 published papers inform the pipeline, distilled into 10 named innovations — every source listed below, because a score you can’t audit is an opinion.
Repository understanding
Test generation
- 2307.13383Predicting Code Coverage without Execution
- 2308.16557Effective Test Generation Using Pre-trained LLMs and Mutation Testing
- 2406.04531TESTEVAL: Benchmarking Large Language Models for Test Case Generation
- 2406.12952Code Agents are State of the Art Software Testers
- 2602.08146Test vs Mutant: Adversarial LLM Agents for Robust Unit Test Generation
Code embeddings & retrieval
Ontology & knowledge graphs
- 2304.02711SPIRES: Structured Prompt Interrogation and Recursive Extraction of Semantics
- 2305.08703Schema-adaptable Knowledge Graph Construction
- 2307.16648LLMs4OL: Large Language Models for Ontology Learning
- 2311.14740AutoKG: Efficient Automated Knowledge Graph Generation
- 2405.19877KNOW: A Real-World Ontology for Knowledge Capture with LLMs
- 2502.13025Agentic Deep Graph Reasoning Yields Self-Organizing Knowledge Networks
- 2503.21902OntoAligner: Comprehensive Toolkit for Ontology Alignment
- 2508.17906FinReflectKG: Agentic Construction and Evaluation of Financial Knowledge Graphs
- 2508.19428Heterogeneous LLM Methods for Ontology Learning
Security & execution safety
- 2502.07049LLMs in Software Security: Vulnerability Detection Techniques and Insights
- 2507.16585LLMxCPG: Vulnerability Detection Through Code Property Graph-Guided LLMs
- 2512.01651Rethinking Cybersecurity Ontology Classification and Evaluation
- 2603.13247ILION: Deterministic Pre-Execution Safety Gates for Agentic AI Systems
Benchmarking
- 2503.07701Automated Benchmark Generation for Repository-Level Coding Tasks
- 2506.09289UTBoost: Rigorous Evaluation of Coding Agents on SWE-Bench
- 2509.16941SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?
- 2603.03823SWE-CI: Evaluating Agent Capabilities via Continuous Integration
Named innovations
- Adversarial test refinement loopTest vs Mutant
- Static coverage prediction modelPredicting Code Coverage without Execution
- LoRA-tuned domain embeddingsLoRACode
- CPG + LLM vulnerability reasoningLLMxCPG
- Agentic financial business-logic graphFinReflectKG
- CI-driven quality evolution curvesSWE-CI
- Git-history-to-benchmark pipelineAutomated Benchmark Generation
- Dual-embedding hybrid searchCodeXEmbed + Node2Vec
- ILION safety gate for generated codeILION
- Developer knowledge-silo detectionRepoGraph + temporal analysis
Where does your codebase stand?
Publish a repository only when you want the repository name, score, and grade to appear publicly. Leaderboard publishing does not grant Hypebase review or benchmark rights.
Get your score.
Paste a public repo for browser analysis, or sign in for temporary private GitHub access. Nothing is saved until you choose.