Show HN: Topos – Structural code quality metrics for agent-written programs

Show HN: Topos – Structural code quality metrics for agent-written programs(krv.ai)

5 points by wayland_jeremy 11 days ago | 1 comment

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.

piyush24rai 11 days ago |

Code review as a bottleneck is definitely the right problem to be solving right now. Integrating this as an MCP server for agents to self evaluate before submitting a PR is a clever use of the protocol. Do you have any benchmarks or examples comparing 'Topos-evaluated' code against standard human-reviewed code in terms of regression rates?