# RepoGenesis: Benchmarking End-to-End Microservice Generation from Readme to Repository

arXiv: https://arxiv.org/abs/2601.13943 · HTML: https://mlsanity.com/paper/2601.13943/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Jan 2026.

## Built on by (most cited first, 11 of 11)

- [ICAE-Bench: Evaluating Coding Agents as Interactive Project Builders](https://mlsanity.com/paper/2607.21217/) (2026)
- [SaaSBench: Exploring the Boundaries of Coding Agents in Long-Horizon Enterprise SaaS Engineering](https://mlsanity.com/paper/2605.17526/) (2026)
- [Repo0: Design-Driven Zero-to-All Code Generation](https://mlsanity.com/paper/2608.19854/) (2026)
- [SolAgent: A Specialized Multi-Agent Framework for Solidity Code Generation](https://mlsanity.com/paper/2601.23009/) (2026)
- [Rule Taxonomy and Evolution in AI IDEs: A Mining and Survey Study](https://mlsanity.com/paper/2606.12231/) (2026)
- [Compact Documentation for Coding Agents: A Benchmark, an Optimizer, and Why It Does Not Transfer](https://mlsanity.com/paper/2609.31587/) (2026)
- [Zero2Repo: Can Coding Agents Build Repositories from Scratch?](https://mlsanity.com/paper/2609.38269/) (2026)
- [E2E-SWE: Benchmarking LLMs on Building Working Codebases from Scratch](https://mlsanity.com/paper/2609.38335/) (2026)
- [AECP: Artifact-Exclusive Communication Protocol for Multi-Agent Code Generation](https://mlsanity.com/paper/2610.06481/) (2026)
- [Large-scale Repository Engineering via Agent-Native Reusable Code Primitives](https://mlsanity.com/paper/2610.09079/) (2026)
- [SWE-Journey: Towards More Realistic Evaluation of Coding Assistants through Long-Horizon, Multi-Turn Interaction](https://mlsanity.com/paper/2610.11559/) (2026)

## Abstract (arXiv)

Large language models and agents have achieved remarkable progress in code generation. However, existing benchmarks focus on isolated function/class-level generation (e.g., ClassEval) or modifications to existing codebases (e.g., SWE-Bench), neglecting complete microservice repository generation that reflects real-world 0-to-1 development workflows. To bridge this gap, we introduce RepoGenesis, the first multilingual benchmark for repository-level end-to-end web microservice generation, comprising 106 repositories (60 Python, 46 Java) across 18 domains and 11 frameworks, with 1,258 API endpoints and 2,335 test cases verified through a "review-rebuttal" quality assurance process. We evaluate open-source agents (e.g., DeepCode) and commercial IDEs (e.g., Cursor) using Pass@1, API Coverage (AC), and Deployment Success Rate (DSR). Results reveal that despite high AC (up to 73.91%) and DSR (up to 100%), the best-performing system achieves only 23.67% Pass@1 on Python and 21.45% on Java, exposing deficiencies in architectural coherence, dependency management, and cross-file consistency. Notably, GenesisAgent-8B, fine-tuned on RepoGenesis (train), achieves performance comparable to GPT-5 mini, demonstrating the quality of RepoGenesis for advancing microservice generation. We release our benchmark at https://github.com/pzy2000/RepoGenesis.