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+# Codebase Optimization & Refactoring Review
+
+## 1. Module Decomposition
+
+Several context modules have grown beyond manageable sizes, making them difficult to navigate and maintain.
+
+*   **`Towerops.Snmp` (~3000 lines)**: This module is acting as a "God Context" for all things SNMP.
+    *   **Recommendation**: Split into sub-contexts like `Towerops.Snmp.Discovery`, `Towerops.Snmp.Queries`, and `Towerops.Snmp.Monitoring`.
+*   **`Towerops.Accounts` (~1900 lines)**: Handles everything from user registration to TOTP device management.
+    *   **Recommendation**: Move TOTP logic to `Towerops.Accounts.TOTP` and session management to `Towerops.Accounts.Sessions`.
+*   **`Towerops.Topology` (~1600 lines)**: Contains complex graph inference logic alongside standard CRUD.
+    *   **Recommendation**: Extract the inference engine logic into `Towerops.Topology.InferenceEngine`.
+
+## 2. DRY Refactoring Opportunities
+
+### SNMP Check Creation
+In `Towerops.Snmp.create_checks_from_discovery`, there is a repetitive pattern for creating checks for sensors, interfaces, processors, and storage.
+
+```elixir
+# Current Pattern
+results = Enum.reduce(snmp_device.sensors, results, fn sensor, acc ->
+  case create_sensor_check(device, sensor) do
+    {:ok, _check} -> Map.update!(acc, :sensors, &(&1 + 1))
+    {:error, reason} -> Map.update!(acc, :errors, &[{:sensor, sensor.id, reason} | &1])
+  end
+end)
+```
+
+**Recommendation**: Create a generic `create_discovered_checks(device, entities, type, check_fun)` helper to reduce boilerplate.
+
+### Topology Evidence Collection
+`collect_lldp_evidence`, `collect_cdp_evidence`, `collect_mac_evidence`, and `collect_arp_evidence` all perform similar transformations.
+
+**Recommendation**: Standardize the evidence collection pipeline. Use a common internal function that takes a query and a transformation mapper.
+
+### Ecto Query Repetition
+Many modules repeat basic query logic like `where(organization_id: ^org_id)`.
+
+**Recommendation**: Implement "Query" modules for each schema (e.g., `Towerops.Devices.DeviceQuery`) containing reusable query fragments that can be composed.
+
+## 3. Functional Pattern Matching vs. Conditionals
+
+### Replace `cond` with Pattern Matching
+In `Towerops.Topology.infer_role_from_capabilities`, a `cond` block is used to match strings in a list.
+
+**Recommendation**: Use multi-clause functions or a more declarative approach.
+```elixir
+defp role_from_cap(["router" | _]), do: :router
+defp role_from_cap(["bridge", "wlan-ap" | _]), do: :wireless
+# ...
+```
+
+### Avoid `if` for Optional Query Filters
+In `Towerops.Snmp.get_sensor_readings`, an `if` statement is used to conditionally add a `where` clause.
+
+**Recommendation**: Use a pipe-friendly helper:
+```elixir
+defp maybe_filter_since(query, nil), do: query
+defp maybe_filter_since(query, since), do: where(query, [r], r.checked_at >= ^since)
+
+# Usage
+query
+|> maybe_filter_since(since)
+|> Repo.all()
+```
+
+## 4. Performance Optimizations
+
+### Batch Database Operations
+In `Towerops.Topology.upsert_link`, evidence records are inserted one-by-one in an `Enum.each` loop.
+
+**Recommendation**: Use `Repo.insert_all` to insert all evidence records in a single round-trip to the database.
+
+### Preloading Strategy
+Some functions perform manual preloads inside loops or deep in the call stack.
+
+**Recommendation**: Ensure associations are preloaded at the edge of the context (the public API) to avoid N+1 queries and redundant database calls.
+
+## 5. Human-Centric Refactoring
+
+### Break Down Large Functions
+Functions like `Towerops.Topology.build_device_lookup` are doing too much in one block.
+
+**Recommendation**: Break these into smaller, named stages:
+1. `fetch_lookup_devices(org_id)`
+2. `map_ips_to_ids(devices)`
+3. `map_names_to_ids(devices)`
+4. `map_macs_to_ids(devices)`
+
+### Consistent Result Handling
+While `Towerops.Result` exists, it isn't used everywhere.
+
+**Recommendation**: Standardize on `{:ok, value} | {:error, reason}` across all context boundaries and use `Towerops.Result` helpers to compose operations.