AI-Powered Development Platform

RepoSmith: Agentic Repo Generation

Built an autonomous CLI that converts natural-language ideas into published GitHub repos with a self-healing loop until all checks pass, plus an eval harness for agent reliability.

January 1, 2026
aipythonfull-stackbackend
01

Context

Modern development increasingly leverages AI assistance, but most tools stop at code generation. RepoSmith pushes the boundary by handling the entire repo lifecycle—from idea to published, tested, and documented GitHub repository—with autonomous iteration.

02

What I Built

An autonomous CLI built with Python and Typer that converts a natural-language idea into a fully published GitHub repo. The system implements a self-healing loop that iterates through build, test, lint, dev boot, and quick start checks until all pass, with full run logging for auditability and replay.

03

Key Decisions

1Built self-healing loop that iterates until build, tests, lint, dev boot, and quick start checks are green
2Designed eval harness with versioned benchmark suites for tracking agent reliability
3Implemented sandboxed verification running checks in Docker for safe automated changes
4Used isolated git branches with re-verification before accepting patches for reproducibility
04

Challenges

Ensuring agent reliability across diverse project types and requirements
Designing a robust self-healing loop that avoids infinite loops on edge cases
Balancing automation with auditability for enterprise use cases
Managing complexity of multi-step verification in isolated environments
05

Outcomes

Achieved reliable repo generation from natural-language prompts
Built comprehensive eval harness tracking success rate, time-to-green, and fix iterations
Implemented safe rollback mechanisms reducing risk from automated changes
Created full audit logging enabling replay and debugging of agent runs
06

Tech Stack

PythonTyperNext.jsDockerGitHub CLI