Repository-aware generation
Scan real project structure, language patterns, service clusters, and app conventions so the generated guidance reflects the repository instead of a generic template.
AI-native engineering workflows
Turn your repository into a structured AI operating system.
Harness Gen scans a codebase, identifies the real structure of your stack, and generates ready-to-use instructions, rules, skills, hooks, and SDLC workflows for tools like Claude, GitHub Copilot, Cursor, and Codex.
Repository scan
FastAPI + React + Python + TypeScript
Detected
Services
8 clusters
Output
Agents
Custom guidance
Workflow
SDLC
Spec → plan → review
Claude
Copilot
Cursor
Codex
What it does
Build a more reliable AI workflow from the code that already exists.
Tool-native outputs
Generate the right files for Claude Code, GitHub Copilot, Cursor, and other environments without wasting time hand-authoring instructions, skills, and rules.
Operational clarity
Add validation, audit baselines, policy checkpoints, and SDLC workflow scaffolding so the AI harness remains aligned as the codebase evolves.
How it works
From repo discovery to production-ready AI guidance.
01
Scan the repository
Harness Gen inspects structure, source languages, app patterns, and dependency clusters.
02
Map the system
It identifies the rules, domains, conventions, and operational boundaries relevant to the project.
03
Generate harness files
It produces instructions, skills, hooks, agents, and SDLC workflow artifacts in the correct format.
04
Validate and refine
Teams can audit drift, enforce standards, and keep AI behavior aligned with project reality.
Why teams use it
Built for modern engineering teams working in complex, multi-language codebases.
Multi-language support
Works across TypeScript, Python, Java, and other dominant stacks without losing project context.
Operational guardrails
Support for validation, drift tracking, maturity scoring, and policy-backed workflow setup.
Scalable AI adoption
Useful for engineering leaders who want consistency, reproducibility, and faster onboarding for AI-assisted work.
Built for clarity
Less guesswork. More predictable AI delivery.
Rather than asking an LLM to invent the repository map, Harness Gen turns the structure into stable, reviewable artifacts. That makes AI more reliable, more reusable, and easier to govern.
Get started