Architecture maps your codebase into named features and shows how work distributes across them. It also powers the architecture multiplier that adjusts performance scores based on structural complexity.
Feature discovery
When architecture analysis is enabled, Navigara runs a multi-phase AI agent per repository that:
- Explores the codebase structure to discover distinct features (e.g.
auth, billing, notifications).
- Organizes each feature into vertical layers — frontend, backend, and data — with specific file paths.
- Maps dependencies between features, showing which parts of the system are coupled.
The agent produces a feature graph: nodes are features with known layers, edges are dependency relationships. This graph is used for both visualization and as input to the performance multiplier.
Commit-to-feature matching
Once features are discovered, every commit is matched to the feature(s) it touches based on the files it changes. This uses path-based scoring:
| Match strategy | Confidence |
|---|
| Exact path match | Highest |
| Directory containment | High |
| Filename affinity | Moderate |
Repository mesh
When multiple repositories are connected to the same organization, their feature graphs are stitched into a repository mesh — a cross-repo dependency map. The mesh emerges from API contracts, shared libraries, and event flows detected by the architect agent.
See Performance > Repository mesh for how the mesh affects scoring.
What you see
All performance and alignment metrics can be grouped by feature, so you can answer questions like:
- Which features are getting the most investment?
- Where is most of the bug-fix work concentrated?
- Is the auth system seeing unplanned churn?
- Which features have the highest structural complexity?
- Where do cross-repository dependencies create leverage?
Architecture analysis is optional and can be enabled per repository. It’s most useful for larger codebases where work naturally spans multiple distinct areas.
