# API Audit: Poindexter Go Library

This document audits the public API of the Poindexter Go library, focusing on design, consistency, documentation, and security best practices for a Go library.

## 1. API Design and Consistency

### 1.1. Naming Conventions

*   **Consistency:** The library generally follows Go's naming conventions (`camelCase` for unexported, `PascalCase` for exported).
*   **Clarity:** Function names are clear and descriptive (e.g., `SortInts`, `SortByKey`, `NewKDTree`).
*   **Minor Inconsistency:** `IsSorted` exists, but `IsSortedStrings` and `IsSortedFloat64s` are more verbose. A more consistent naming scheme might be `IntsAreSorted`, `StringsAreSorted`, etc., to mirror the standard library's `sort` package.

### 1.2. Generics

*   **Effective Use:** The use of generics in `SortBy` and `SortByKey` is well-implemented and improves type safety and usability.
*   **`KDPoint`:** The `KDPoint` struct effectively uses generics for its `Value` field, allowing users to associate any data type with a point.

### 1.3. Error Handling

*   **Exported Errors:** The library exports sentinel errors (`ErrEmptyPoints`, `ErrDimMismatch`, etc.), which is a good practice, allowing users to check for specific error conditions.
*   **Constructor Errors:** The `NewKDTree` constructor correctly returns an error value, forcing callers to handle potential issues during tree creation.

### 1.4. Options Pattern

*   **`NewKDTree`:** The use of the options pattern with `KDOption` functions (`WithMetric`, `WithBackend`) is a great choice. It provides a flexible and extensible way to configure the `KDTree` without requiring a large number of constructor parameters.

## 2. Documentation

*   **Package-Level:** The package-level documentation is good, providing a clear overview of the library's features.
*   **Exported Symbols:** All exported functions, types, and constants have clear and concise documentation comments.
*   **Examples:** The `README.md` includes excellent quick-start examples, and the `examples/` directory provides more detailed, runnable examples.

## 3. Security

### 3.1. Input Validation

*   **`NewKDTree`:** The constructor performs thorough validation of its inputs, checking for empty point sets, zero dimensions, and dimensional mismatches. This prevents the creation of invalid `KDTree` instances.
*   **`KDTree` Methods:** Methods like `Nearest` and `KNearest` validate the dimensionality of the query vector, preventing panics or incorrect behavior.
*   **`DeleteByID`:** This method correctly handles cases where the ID is not found or is empty.

### 3.2. Panics

*   The public API appears to be free of potential panics. The library consistently uses error returns and input validation to handle exceptional cases.

## 4. Recent API Design and Ergonomics Improvements

### 4.1. "God Class" Refactoring in `kdtree_analytics.go`

The file `kdtree_analytics.go` exhibited "God Class" characteristics, combining core tree analytics with unrelated responsibilities like peer trust scoring and NAT metrics. This made the code difficult to maintain and understand.

**Changes Made:**
To address the "God Class" issue, `kdtree_analytics.go` was decomposed into three distinct files:

*   `kdtree_analytics.go`: Now contains only the core tree analytics.
*   `peer_trust.go`: Contains the peer trust scoring logic.
*   `nat_metrics.go`: Contains the NAT-related metrics.

### 4.2. Method Naming Improvements

The method `ComputeDistanceDistribution` in `kdtree.go` was inconsistently named, as it actually computed axis-based distributions, not distance distributions.

**Changes Made:**
Renamed the `ComputeDistanceDistribution` method to `ComputeAxisDistributions` to more accurately reflect its functionality.

### 4.3. Refactored `kdtree.go`

Updated `kdtree.go` to use the new, more focused modules. Removed the now-unnecessary `ResetAnalytics` methods, which were tightly coupled to the old analytics implementation.

## Summary and Recommendations

The Poindexter library's public API is well-designed, consistent, and follows Go best practices. The use of generics, the options pattern, and clear error handling make it a robust and user-friendly library. Recent refactoring efforts have improved modularity and maintainability.

**Recommendations:**

1.  **Naming Consistency:** Consider renaming `IsSorted`, `IsSortedStrings`, and `IsSortedFloat64s` to `IntsAreSorted`, `StringsAreSorted`, and `Float64sAreSorted` to align more closely with the standard library's `sort` package.
2.  **Defensive Copying:** The `Points()` method returns a copy of the internal slice, which is excellent. Ensure that any future methods that expose internal state also return copies to prevent mutation by callers.
3.  **Continued Modularization:** The recent decomposition of `kdtree_analytics.go` is a positive step. Continue to evaluate the codebase for opportunities to separate concerns and improve maintainability.