Lower macOS requirement from 15.0 to 14.0

Based on API usage analysis, Peekaboo only requires macOS 14.0 (Sonoma), not macOS 15.0 (Sequoia). The APIs we use:
- SCScreenshotManager.captureImage: macOS 14.0+
- configuration.shouldBeOpaque: macOS 14.0+
- Typed throws syntax: Works with macOS 14.0

This change makes Peekaboo available to more users who haven't upgraded to Sequoia yet.

Also fixed warning about undefined modelName in AI providers by using nullish coalescing.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

CHANGELOG.md

@@ -30,7 +30,7 @@ Peekaboo MCP is now production-ready! This release marks the culmination of exte
 - Robust permission handling for Screen Recording and Accessibility
 
 ### Requirements
-- macOS 15.0 or later (Sequoia)
+- macOS 14.0 or later (Sonoma)
 - Node.js 18 or later
 - Screen Recording permission (for capture features)
 - Accessibility permission (optional, for foreground window detection)

README.md

@@ -4,7 +4,7 @@
 
 [![npm version](https://badge.fury.io/js/%40steipete%2Fpeekaboo-mcp.svg)](https://www.npmjs.com/package/@steipete/peekaboo-mcp)
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
-[![macOS](https://img.shields.io/badge/macOS-15.0%2B-blue.svg)](https://www.apple.com/macos/)
+[![macOS](https://img.shields.io/badge/macOS-14.0%2B-blue.svg)](https://www.apple.com/macos/)
 [![Node.js](https://img.shields.io/badge/node-%3E%3D20.0.0-brightgreen.svg)](https://nodejs.org/)
 
 Peekaboo is a macOS-only MCP server that enables AI agents to capture screenshots of applications, windows, or the entire system, with optional visual question answering through local or remote AI models.
@@ -33,7 +33,7 @@ Read more about the design philosophy and implementation details in the [blog po
 
 ### Requirements
 
-- **macOS 15.0+** (Sequoia or later)
+- **macOS 14.0+** (Sonoma or later)
 - **Node.js 20.0+**
 - **Screen Recording Permission** (you'll be prompted on first use)
 

peekaboo-cli/Package.swift

@@ -4,7 +4,7 @@ import PackageDescription
 let package = Package(
     name: "peekaboo",
     platforms: [
-        .macOS(.v15)
+        .macOS(.v14)
     ],
     products: [
         .executable(

peekaboo-cli/Sources/peekaboo/main.swift

@@ -2,7 +2,7 @@ import ArgumentParser
 import Foundation
 
 @main
-@available(macOS 10.15, *)
+@available(macOS 14.0, *)
 struct PeekabooCommand: AsyncParsableCommand {
     static let configuration = CommandConfiguration(
         commandName: "peekaboo",

src/utils/ai-providers.ts

@@ -106,6 +106,9 @@ async function analyzeWithOllama(
 
   logger.debug({ model, baseUrl }, "Analyzing image with Ollama");
 
+  // Default to describing the image if no question is provided
+  const prompt = question.trim() || "Please describe what you see in this image.";
+
   const response = await fetch(`${baseUrl}/api/generate`, {
     method: "POST",
     headers: {
@@ -113,7 +116,7 @@ async function analyzeWithOllama(
     },
     body: JSON.stringify({
       model,
-      prompt: question,
+      prompt,
       images: [imageBase64],
       stream: false,
     }),
@@ -147,13 +150,16 @@ async function analyzeWithOpenAI(
 
   const openai = new OpenAI({ apiKey });
 
+  // Default to describing the image if no question is provided
+  const prompt = question.trim() || "Please describe what you see in this image.";
+
   const response = await openai.chat.completions.create({
     model: model || "gpt-4o",
     messages: [
       {
         role: "user",
         content: [
-          { type: "text", text: question },
+          { type: "text", text: prompt },
           {
             type: "image_url",
             image_url: {

tests/unit/tools/analyze-edge-cases.test.ts

@@ -37,7 +37,7 @@ describe("Analyze Tool - Edge Cases", () => {
   });
 
   describe("Empty question handling", () => {
-    it("should handle empty string question", async () => {
+    it("should handle empty string question with default prompt", async () => {
       mockParseAIProviders.mockReturnValue([
         { provider: "ollama", model: "llava:latest" }
       ]);
@@ -49,8 +49,8 @@ describe("Analyze Tool - Edge Cases", () => {
       
       mockReadImageAsBase64.mockResolvedValue("base64imagedata");
       
-      // Mock Ollama returning "No response from Ollama" for empty question
-      mockAnalyzeImageWithProvider.mockResolvedValue("No response from Ollama");
+      // Mock Ollama returning a description of the image
+      mockAnalyzeImageWithProvider.mockResolvedValue("This image shows a desktop window with various UI elements.");
 
       const result = await analyzeToolHandler(
         { 
@@ -69,11 +69,11 @@ describe("Analyze Tool - Edge Cases", () => {
       );
 
       expect(result.content[0].type).toBe("text");
-      expect(result.content[0].text).toBe("No response from Ollama");
+      expect(result.content[0].text).toBe("This image shows a desktop window with various UI elements.");
       expect(result.model_used).toBe("ollama/llava:latest");
     });
 
-    it("should handle whitespace-only question", async () => {
+    it("should handle whitespace-only question with default prompt", async () => {
       mockParseAIProviders.mockReturnValue([
         { provider: "ollama", model: "llava:latest" }
       ]);
@@ -84,7 +84,7 @@ describe("Analyze Tool - Edge Cases", () => {
       });
       
       mockReadImageAsBase64.mockResolvedValue("base64imagedata");
-      mockAnalyzeImageWithProvider.mockResolvedValue("No response from Ollama");
+      mockAnalyzeImageWithProvider.mockResolvedValue("This image shows a screenshot of an application.");
 
       const result = await analyzeToolHandler(
         { 
@@ -102,10 +102,10 @@ describe("Analyze Tool - Edge Cases", () => {
         mockLogger,
       );
 
-      expect(result.content[0].text).toBe("No response from Ollama");
+      expect(result.content[0].text).toBe("This image shows a screenshot of an application.");
     });
 
-    it("should handle question with only newlines", async () => {
+    it("should handle question with only newlines with default prompt", async () => {
       mockParseAIProviders.mockReturnValue([
         { provider: "ollama", model: "llava:latest" }
       ]);
@@ -116,7 +116,7 @@ describe("Analyze Tool - Edge Cases", () => {
       });
       
       mockReadImageAsBase64.mockResolvedValue("base64imagedata");
-      mockAnalyzeImageWithProvider.mockResolvedValue("No response from Ollama");
+      mockAnalyzeImageWithProvider.mockResolvedValue("This image displays a user interface with multiple sections.");
 
       const result = await analyzeToolHandler(
         { 
@@ -134,7 +134,7 @@ describe("Analyze Tool - Edge Cases", () => {
         mockLogger,
       );
 
-      expect(result.content[0].text).toBe("No response from Ollama");
+      expect(result.content[0].text).toBe("This image displays a user interface with multiple sections.");
     });
   });
 

tests/unit/utils/ai-providers.test.ts

@@ -335,6 +335,51 @@ describe("AI Providers Utility", () => {
       expect(result).toBe("No response from Ollama");
     });
 
+    it("should use default prompt for empty question with Ollama", async () => {
+      (global.fetch as vi.Mock).mockResolvedValueOnce({
+        ok: true,
+        json: async () => ({ response: "This image shows a window with text content." }),
+      });
+      const result = await analyzeImageWithProvider(
+        { provider: "ollama", model: "llava" },
+        "path/img.png",
+        imageBase64,
+        "", // Empty question
+        mockLogger,
+      );
+      expect(result).toBe("This image shows a window with text content.");
+      const fetchCall = (global.fetch as vi.Mock).mock.calls[0];
+      const body = JSON.parse(fetchCall[1].body);
+      expect(body.prompt).toBe("Please describe what you see in this image.");
+    });
+
+    it("should use default prompt for whitespace-only question with OpenAI", async () => {
+      process.env.OPENAI_API_KEY = "test-key";
+      mockChatCompletionsCreate.mockResolvedValueOnce({
+        choices: [{ message: { content: "This image displays a user interface." } }],
+      });
+
+      const result = await analyzeImageWithProvider(
+        { provider: "openai", model: "gpt-4o" },
+        "path/img.png",
+        imageBase64,
+        "   ", // Whitespace-only question
+        mockLogger,
+      );
+      expect(result).toBe("This image displays a user interface.");
+      expect(mockChatCompletionsCreate).toHaveBeenCalledWith(
+        expect.objectContaining({
+          messages: expect.arrayContaining([
+            expect.objectContaining({
+              content: expect.arrayContaining([
+                { type: "text", text: "Please describe what you see in this image." },
+              ]),
+            }),
+          ]),
+        }),
+      );
+    });
+
     it("should throw error for anthropic provider (not implemented)", async () => {
       await expect(
         analyzeImageWithProvider(