| name | matt-improve-codebase-architecture |
| description | Explore a codebase to find opportunities for architectural improvement, focusing on making the codebase more testable by deepening shallow modules. Use when user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more AI-navigable. |
| agent | matt |
| user-invocable | false |
| metadata | {"pattern":"reviewer, inversion, generator"} |
Improve Codebase Architecture
Explore a codebase like an AI would, surface architectural friction, discover opportunities for improving testability, and propose module-deepening refactors as GitHub issue RFCs.
A deep module (John Ousterhout, "A Philosophy of Software Design") has a small interface hiding a large implementation. Deep modules are more testable, more AI-navigable, and let you test at the boundary instead of inside.
Process
1. Explore the codebase
Use the Agent tool with subagent_type=Explore to navigate the codebase naturally. Do NOT follow rigid heuristics — explore organically and note where you experience friction:
- Where does understanding one concept require bouncing between many small files?
- Where are modules so shallow that the interface is nearly as complex as the implementation?
- Where have pure functions been extracted just for testability, but the real bugs hide in how they're called?
- Where do tightly-coupled modules create integration risk in the seams between them?
- Which parts of the codebase are untested, or hard to test?
The friction you encounter IS the signal.
2. Present candidates
Present a numbered list of deepening opportunities. For each candidate, show:
- Cluster: Which modules/concepts are involved
- Why they're coupled: Shared types, call patterns, co-ownership of a concept
- Dependency category: See REFERENCE.md for the four categories
- Test impact: What existing tests would be replaced by boundary tests
Do NOT propose interfaces yet. Ask the user: "Which of these would you like to explore?"
3. User picks a candidate
4. Frame the problem space
Before spawning sub-agents, write a user-facing explanation of the problem space for the chosen candidate:
- The constraints any new interface would need to satisfy
- The dependencies it would need to rely on
- A rough illustrative code sketch to make the constraints concrete — this is not a proposal, just a way to ground the constraints
Show this to the user, then immediately proceed to Step 5. The user reads and thinks about the problem while the sub-agents work in parallel.
5. Design multiple interfaces
Spawn 3+ sub-agents in parallel using the Agent tool. Each must produce a radically different interface for the deepened module.
Prompt each sub-agent with a separate technical brief (file paths, coupling details, dependency category, what's being hidden). This brief is independent of the user-facing explanation in Step 4. Give each agent a different design constraint:
- Agent 1: "Minimize the interface — aim for 1-3 entry points max"
- Agent 2: "Maximize flexibility — support many use cases and extension"
- Agent 3: "Optimize for the most common caller — make the default case trivial"
- Agent 4 (if applicable): "Design around the ports & adapters pattern for cross-boundary dependencies"
Each sub-agent outputs:
- Interface signature (types, methods, params)
- Usage example showing how callers use it
- What complexity it hides internally
- Dependency strategy (how deps are handled — see REFERENCE.md)
- Trade-offs
Present designs sequentially, then compare them in prose.
After comparing, give your own recommendation: which design you think is strongest and why. If elements from different designs would combine well, propose a hybrid. Be opinionated — the user wants a strong read, not just a menu.
6. User picks an interface (or accepts recommendation)
7. Create GitHub issue
Create a refactor RFC as a GitHub issue using gh issue create. Use the template in REFERENCE.md. Do NOT ask the user to review before creating — just create it and share the URL.
