Topos – Structural code quality metrics for agent-written programs
Code review is the new bottleneck. "Tests passing" is no longer sufficient to trust the changes, and the (human) cost of evaluating the quality and robustness of new agent-written contributions is skyrocketing. We built Topos to evaluate code quality based on the structural properties of the programs themselves. We map your files to graphs (AST, CFG, CPG, MDG) and calculate metrics that can characterize how simple, composable, or secure your programs are. Agents can use this tool as they write and optimize based on your preferences. And yes, the inspiration for the repository is from…
Topos – Structural code quality metrics for agent-written programs launched on June 25, 2026 with 5 votes, #2,466 of 22,647 launches that month and more than 75% of that year's launches.
What it does
Correctness is table stakes. Topos evaluates the structural quality of agent-written code so working diffs do not become long-term codebase debt.
Why “technically correct” is the lowest form of success in the agentic era. Krv-Labs/topos is open source Star — or jump straight to installation . Every engineer who has used Claude Code or let an agent loose on their repo knows the exact flavor of dread that comes next: a notification pops up, and you are staring at an 800-line diff spanning 14 files, generated in under five minutes. The CI pipeline is blindingly green. The micro-syntax is flawless. But as you start scrolling, reality hits you: we are now approving code we don't actually understand. The cognitive load is asymmetrical. The agent solved the immediate ticket, sure, but it did so by hallucinating a slightly worse copy of a…from krv.ai
In the maker’s words, at launch
Code review is the new bottleneck. "Tests passing" is no longer sufficient to trust the changes, and the (human) cost of evaluating the quality and robustness of new agent-written contributions is skyrocketing. We built Topos to evaluate code quality based on the structural properties of the programs themselves. We…
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