Topos – Structural code quality metrics for agent-written programs

Name: Topos – Structural code quality metrics for agent-written programs
Availability: InStock
Author: wayland_jeremy

by wayland_jeremy·Jun 25, 2026·5 points·1 comment

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AI Analysis

●●SolidBig BrainShip It

Structural code metrics with Bronze/Silver/Gold medals when SonarQube only does pass/fail.

Strengths

•Addresses real agentic spray problem where tests pass but architecture degrades
•Three independent pillars (Simple, Composable, Secure) scored per file, not just repo-level
•Category theory foundation with Heyting algebra subobject classifier for medal states

Weaknesses

•Competes with SonarQube, CodeClimate, Codacy in crowded code quality space
•Category theory framing may intimidate teams who just want actionable metrics

Post Description

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 category theory: this is inspired by a topos for program evaluation, that comes equipped with objects (program representations), morphisms (maps on graphs), probes, profunctors, test-coverage metrics, and a custom subobject classifier (Heyting algebra generated by the 3 pillars of evaluation) that affords a highly structured framework for awarding medals for program quality.

GitHub: https://github.com/Krv-Labs/topos

Open Source. BSD-3 License. CLI, MCP Server & VS Code Extension.