Codebase Readiness
You've seen it: an agent rewrites a file, the tests pass, but the code doesn't follow your conventions. Or worse, there are no tests to catch what it broke. Weak test coverage, unclear architecture, missing type safety, no feedback loops. These aren't minor inconveniences. They're the reason agents produce drift instead of value.
This free assessment scores your repo across the 8 dimensions that matter most for AI-assisted development and gives you a prioritized roadmap to close the gaps.
A codebase readiness assessment evaluates how well your repository supports AI-assisted development. It measures test coverage, architecture clarity, type safety, feedback loops, and five other dimensions that determine whether AI agents produce useful output or compound drift.
Install
The assessment is an agent skill. Enter your email and I'll send you both ways to install it, how to run it, and what your score means.
I'll send the install instructions to your inbox. You'll also get practical notes on AI engineering and agent architecture. No spam. Unsubscribe anytime.
The assessment runs locally against your repo. Nothing is sent externally.
Built by Damian Galarza — 15+ years building production software, former CTO (scaled 0→50+), currently shipping AI features daily as a Senior SWE.
Dimensions
Eight dimensions benchmarked against teams shipping 1,000+ AI-generated PRs per week. Each dimension gets a weighted score contributing to your overall rating (0-100).
01
Coverage, speed, reliability. Agents need fast, trustworthy feedback to know if their changes work. Without it, they guess.
02
Layering, dependency direction, separation of concerns. Agents replicate existing patterns. Without clear boundaries, agent output drifts across concerns and couples things that shouldn't be coupled.
03
Static analysis, type coverage, schema validation. Types constrain the solution space. Without them, agents make changes that compile but fail silently at runtime.
04
Linting, CI speed, error messages. Agents learn from error output. Without quality feedback, agents repeat the same mistakes and you spend human time catching what automation should catch.
05
CLAUDE.md quality, architecture docs, inline context. This is how agents understand intent. Without it, agents produce code that passes every check but misses the point.
06
Outdated packages, security vulnerabilities, lockfile hygiene. Without healthy dependencies, agents inherit unpredictable behavior they can't reason about or debug.
07
Setup scripts, containerization, reproducibility. Without a consistent environment, agents produce changes that work locally and break everywhere else.
08
Formatting, naming conventions, structural patterns. Without consistency, every agent change looks like it was written by a different developer.
Sample output
Here's what a real assessment looks like. This Rails codebase scored 46/100 — strong code clarity, but documentation and feedback loop gaps that limit agent effectiveness.
| Dimension | Weight | Score |
|---|---|---|
| Test Foundation | 25% | 57/100 |
| Documentation & Context | 15% | 14/100 |
| Code Clarity | 15% | 82/100 |
| Architecture Clarity | 15% | 55/100 |
| Feedback Loops | 10% | 25/100 |
| Type Safety | 10% | 21/100 |
| Consistency & Conventions | 5% | 25/100 |
| Change Safety | 5% | 35/100 |
Output
Fit
From the clients
“Working with Damian was one of the most productive technical sessions we've had…
He quickly understood where we were with AI tooling and gave us immediately actionable advice, not generic frameworks. He identified gaps we hadn't considered, walked us through how he architects agent loops in production, and helped us think through our product-level agent strategy without over-engineering it. If you're a technical founder trying to move faster with AI, Damian is the person to talk to.”
Will Wallace
Co-Founder, Rebolt
Next steps
The roadmap tells you exactly what to fix and in what order. For documentation gaps, the companion agent-ready skill scaffolds AGENTS.md, a CLAUDE.md compatibility symlink, ARCHITECTURE.md, docs/DOMAIN.md, docs/README.md, and a starter ADR. If your team has the bandwidth, you can close most gaps on your own.
Foundation Sprint $12k • Retainer $15k–$60k/mo
Engagements start with a 2-week Foundation Sprint that produces an architectural assessment and one shipped foundation piece. From there, extend into a retainer at the intensity your team needs — Advisory, Embedded, or Full — so your team ships confidently with AI, not just a few power users.
Writing
Context on why codebase readiness matters and how it connects to production AI workflows.
FAQ
A codebase readiness assessment evaluates how well your repository supports AI-assisted development. It scores your repo across 8 dimensions (test foundation, architecture clarity, type safety, feedback loops, documentation, dependency health, dev environment, and code consistency) and produces a prioritized improvement roadmap.
Run the assessment. You'll get a score from 0-100 with a band rating: Agent-Ready (80+), Strong (60-79), Developing (40-59), or Foundation (below 40). The per-dimension breakdown shows exactly where your strengths and gaps are.
Eight dimensions benchmarked against teams shipping 1,000+ AI-generated PRs per week: test coverage and speed, architecture layering, type safety, CI and linting feedback loops, CLAUDE.md and documentation quality, dependency health, development environment reproducibility, and code formatting consistency.
No. The assessment runs entirely inside Claude Code on your local machine. Your code never leaves your environment.
Claude Code, or any tool that supports agent skills. Enter your email above and I'll send both install methods, npx and the Claude plugin marketplace, along with how to run it and what the score means.
That's the point of running it. The assessment produces a prioritized improvement roadmap ordered by impact. Most teams can close the highest-impact gaps on their own. For teams that want hands-on help, a Production AI Retainer works through these gaps on your actual codebase.
Run the assessment first. If the results raise questions or you want help prioritizing, book a free intro call. We'll look at your score together and figure out the right next step.
No pitch. No pressure. Just a conversation about what the numbers mean for your team.