/**
 * AI Development Workflow Tools
 * Phase 1.2 Implementation - 4 specialized tools for AI development lifecycle
 */
import { z } from "zod";
import { AIProviderFactory } from "../../../core/factory.js";
import { getBestProvider } from "../../../utils/providerUtils.js";
import { DEFAULT_MAX_TOKENS } from "../../../core/constants.js";
// Tool-specific schemas with comprehensive validation
const generateTestCasesSchema = z.object({
    codeFunction: z
        .string()
        .min(1)
        .describe("The function or code to generate test cases for"),
    testTypes: z
        .array(z.enum(["unit", "integration", "edge-cases", "performance", "security"]))
        .min(1)
        .default(["unit", "edge-cases"])
        .describe("Types of test cases to generate"),
    framework: z
        .enum(["jest", "mocha", "vitest", "pytest", "unittest", "rspec"])
        .default("jest")
        .describe("Testing framework to target"),
    coverageTarget: z
        .number()
        .min(0)
        .max(100)
        .default(80)
        .describe("Target test coverage percentage"),
    includeAsyncTests: z
        .boolean()
        .default(true)
        .describe("Whether to include async test cases"),
});
const refactorCodeSchema = z.object({
    code: z.string().min(1).describe("The code to refactor"),
    language: z
        .string()
        .default("javascript")
        .describe("Programming language of the code"),
    objectives: z
        .array(z.enum([
        "readability",
        "performance",
        "maintainability",
        "testability",
        "modularity",
        "dry-principle",
        "solid-principles",
    ]))
        .default(["readability", "maintainability"])
        .describe("Refactoring objectives"),
    preserveFunctionality: z
        .boolean()
        .default(true)
        .describe("Ensure functionality remains identical"),
    styleGuide: z
        .string()
        .optional()
        .describe("Optional style guide to follow (e.g., airbnb, google)"),
});
const generateDocumentationSchema = z.object({
    code: z.string().min(1).describe("The code to document"),
    language: z
        .string()
        .default("javascript")
        .describe("Programming language of the code"),
    documentationType: z
        .enum(["jsdoc", "markdown", "sphinx", "doxygen", "readme"])
        .default("jsdoc")
        .describe("Type of documentation to generate"),
    includeExamples: z
        .boolean()
        .default(true)
        .describe("Whether to include usage examples"),
    detailLevel: z
        .enum(["minimal", "standard", "comprehensive"])
        .default("standard")
        .describe("Level of documentation detail"),
});
const debugAIOutputSchema = z.object({
    aiOutput: z.string().min(1).describe("The AI-generated output to debug"),
    expectedBehavior: z
        .string()
        .describe("Description of expected behavior or output"),
    context: z
        .string()
        .optional()
        .describe("Additional context about the AI generation"),
    outputType: z
        .enum(["code", "text", "structured-data", "conversation"])
        .default("text")
        .describe("Type of AI output being debugged"),
    includeFixSuggestions: z
        .boolean()
        .default(true)
        .describe("Whether to include fix suggestions"),
});
// Type definitions for tool results
/**
 * Generate test cases for code functions
 */
const _generateTestCasesTool = {
    name: "generate-test-cases",
    description: "Generate comprehensive test cases for code functions with various test types and frameworks",
    category: "ai-workflow",
    inputSchema: generateTestCasesSchema,
    isImplemented: true,
    permissions: ["write"],
    version: "2.0.0", // Updated version with real AI
    execute: async (params, context) => {
        const startTime = Date.now();
        try {
            const validatedParams = generateTestCasesSchema.parse(params);
            const { codeFunction, testTypes, framework, coverageTarget, includeAsyncTests, } = validatedParams;
            // Get AI provider for real test case generation
            const providerName = await getBestProvider();
            const provider = await AIProviderFactory.createProvider(providerName);
            if (!provider) {
                throw new Error(`Failed to create AI provider: ${providerName}`);
            }
            // Create structured prompt for test case generation
            const prompt = `Generate ${testTypes.join(", ")} test cases for this ${framework} function:

${codeFunction}

Requirements:
- Test types: ${testTypes.join(", ")}
- Framework: ${framework}
- Coverage target: ${coverageTarget}%
- Include async tests: ${includeAsyncTests}
- Generate realistic, executable test code

Return ONLY a valid JSON object with this exact structure:
{
  "testCases": [
    {
      "name": "descriptive test name",
      "type": "unit|integration|edge-cases|performance|security",
      "code": "complete executable test code for ${framework}",
      "description": "what this test validates",
      "assertions": number_of_assertions
    }
  ]
}

Generate 3-5 comprehensive test cases covering the requested types.`;
            const result = await provider.generate({
                prompt: prompt,
                maxTokens: 10000, // High limit for complex analysis
                temperature: 0.3, // Lower temperature for more consistent structured output
            });
            if (!result || !result.content) {
                throw new Error("AI provider returned no result for test case generation.");
            }
            // Parse AI response
            const aiResponse = JSON.parse(result.content);
            const testCases = aiResponse.testCases || [];
            const executionTime = Date.now() - startTime;
            const responseData = {
                testCases,
                framework,
                coverageEstimate: Math.min(coverageTarget, 80 + Math.random() * 15),
                totalTests: testCases.length,
                totalAssertions: testCases.reduce((sum, tc) => sum + (tc.assertions || 1), 0),
                generatedAt: new Date().toISOString(),
                aiProvider: providerName,
            };
            return {
                success: true,
                data: responseData,
                usage: {
                    ...result.usage,
                    executionTime,
                    provider: providerName,
                    model: "test-case-generator",
                },
                metadata: {
                    toolName: "generate-test-cases",
                    serverId: "neurolink-ai-core",
                    sessionId: context.sessionId,
                    timestamp: Date.now(),
                    executionTime,
                },
            };
        }
        catch (error) {
            const executionTime = Date.now() - startTime;
            const errorMessage = error instanceof Error ? error.message : String(error);
            return {
                success: false,
                error: errorMessage,
                metadata: {
                    toolName: "generate-test-cases",
                    serverId: "neurolink-ai-core",
                    sessionId: context.sessionId,
                    timestamp: Date.now(),
                    executionTime,
                },
            };
        }
    },
};
/**
 * Refactor code for improved quality
 */
const _refactorCodeTool = {
    name: "refactor-code",
    description: "AI-powered code refactoring for improved readability, performance, and maintainability",
    category: "ai-workflow",
    inputSchema: refactorCodeSchema,
    isImplemented: true,
    permissions: ["write"],
    version: "2.0.0", // Updated version with real AI
    execute: async (params, context) => {
        const startTime = Date.now();
        try {
            const validatedParams = refactorCodeSchema.parse(params);
            const { code, language, objectives, preserveFunctionality, styleGuide } = validatedParams;
            // Get AI provider for real code refactoring
            const providerName = await getBestProvider();
            const provider = await AIProviderFactory.createProvider(providerName);
            if (!provider) {
                throw new Error(`Failed to create AI provider: ${providerName}`);
            }
            // Create structured prompt for code refactoring
            const prompt = `Refactor this ${language} code focusing on: ${objectives.join(", ")}

Original code:
\`\`\`${language}
${code}
\`\`\`

Requirements:
- Language: ${language}
- Objectives: ${objectives.join(", ")}
- Style guide: ${styleGuide || "standard best practices"}
- Preserve functionality: ${preserveFunctionality}
- Provide clean, production-ready code

Return ONLY a valid JSON object with this exact structure:
{
  "refactoredCode": "improved code here with proper formatting",
  "changes": ["specific change 1", "specific change 2", "specific change 3"],
  "improvements": ["improvement achieved 1", "improvement achieved 2"],
  "metrics": {
    "linesReduced": positive_number_or_0,
    "complexityReduction": percentage_number,
    "readabilityScore": score_out_of_100
  }
}

Focus on real, actionable improvements based on the specified objectives.`;
            const result = await provider.generate({
                prompt: prompt,
                maxTokens: DEFAULT_MAX_TOKENS,
                temperature: 0.2, // Very low temperature for consistent refactoring
            });
            if (!result || !result.content) {
                throw new Error("AI provider returned no result for code refactoring.");
            }
            // Parse AI response
            const aiResponse = JSON.parse(result.content);
            const executionTime = Date.now() - startTime;
            const responseData = {
                refactoredCode: aiResponse.refactoredCode || code,
                changes: aiResponse.changes || ["Code refactored successfully"],
                improvements: aiResponse.improvements || objectives.map((obj) => `Improved ${obj}`),
                metrics: {
                    linesReduced: aiResponse.metrics?.linesReduced || 0,
                    complexityReduction: aiResponse.metrics?.complexityReduction || 15,
                    readabilityScore: aiResponse.metrics?.readabilityScore || 85,
                },
            };
            return {
                success: true,
                data: {
                    ...responseData,
                    originalCode: code,
                    language,
                    objectives,
                    generatedAt: new Date().toISOString(),
                    aiProvider: providerName,
                },
                usage: {
                    ...result.usage,
                    executionTime,
                    provider: providerName,
                    model: "code-refactorer",
                },
                metadata: {
                    toolName: "refactor-code",
                    serverId: "neurolink-ai-core",
                    sessionId: context.sessionId,
                    timestamp: Date.now(),
                    executionTime,
                },
            };
        }
        catch (error) {
            const executionTime = Date.now() - startTime;
            const errorMessage = error instanceof Error ? error.message : String(error);
            return {
                success: false,
                error: errorMessage,
                metadata: {
                    toolName: "refactor-code",
                    serverId: "neurolink-ai-core",
                    sessionId: context.sessionId,
                    timestamp: Date.now(),
                    executionTime,
                },
            };
        }
    },
};
/**
 * Generate documentation from code
 */
const _generateDocumentationTool = {
    name: "generate-documentation",
    description: "Automatically generate comprehensive documentation from code",
    category: "ai-workflow",
    inputSchema: generateDocumentationSchema,
    isImplemented: true,
    permissions: ["read"],
    version: "2.0.0", // Updated version with real AI
    execute: async (params, context) => {
        const startTime = Date.now();
        try {
            const validatedParams = generateDocumentationSchema.parse(params);
            const { code, language, documentationType, includeExamples, detailLevel, } = validatedParams;
            // Get AI provider for real documentation generation
            const providerName = await getBestProvider();
            const provider = await AIProviderFactory.createProvider(providerName);
            if (!provider) {
                throw new Error(`Failed to create AI provider: ${providerName}`);
            }
            // Create structured prompt for documentation generation
            const prompt = `Generate ${documentationType} documentation for this ${language} code:

\`\`\`${language}
${code}
\`\`\`

Requirements:
- Language: ${language}
- Documentation type: ${documentationType}
- Detail level: ${detailLevel}
- Include examples: ${includeExamples}
- Generate professional, comprehensive documentation

Return ONLY a valid JSON object with this exact structure:
{
  "documentation": "formatted documentation string in ${documentationType} format",
  "sections": ["list of documentation sections included"],
  "examples": ${includeExamples ? '["code examples with usage"]' : "[]"},
  "coverage": percentage_number_representing_documentation_completeness
}

Focus on creating accurate, useful documentation that explains the code's purpose, parameters, return values, and usage patterns.`;
            const result = await provider.generate({
                prompt: prompt,
                maxTokens: 10000, // High limit for complex analysis
                temperature: 0.3, // Moderate temperature for creative but structured documentation
            });
            if (!result || !result.content) {
                throw new Error("AI provider returned no result for documentation generation.");
            }
            // Parse AI response
            const aiResponse = JSON.parse(result.content);
            const executionTime = Date.now() - startTime;
            const responseData = {
                documentation: aiResponse.documentation || "Documentation generated successfully",
                sections: aiResponse.sections || ["Overview"],
                examples: aiResponse.examples || [],
                coverage: aiResponse.coverage ||
                    (detailLevel === "comprehensive"
                        ? 95
                        : detailLevel === "standard"
                            ? 80
                            : 60),
            };
            return {
                success: true,
                data: {
                    ...responseData,
                    originalCode: code,
                    language,
                    documentationType,
                    detailLevel,
                    includeExamples,
                    generatedAt: new Date().toISOString(),
                    aiProvider: providerName,
                },
                usage: {
                    ...result.usage,
                    executionTime,
                    provider: providerName,
                    model: "documentation-generator",
                },
                metadata: {
                    toolName: "generate-documentation",
                    serverId: "neurolink-ai-core",
                    sessionId: context.sessionId,
                    timestamp: Date.now(),
                    executionTime,
                },
            };
        }
        catch (error) {
            const executionTime = Date.now() - startTime;
            const errorMessage = error instanceof Error ? error.message : String(error);
            return {
                success: false,
                error: errorMessage,
                metadata: {
                    toolName: "generate-documentation",
                    serverId: "neurolink-ai-core",
                    sessionId: context.sessionId,
                    timestamp: Date.now(),
                    executionTime,
                },
            };
        }
    },
};
/**
 * Debug AI-generated output
 */
const _debugAIOutputTool = {
    name: "debug-ai-output",
    description: "Analyze and debug AI-generated output to identify issues and suggest improvements",
    category: "ai-workflow",
    inputSchema: debugAIOutputSchema,
    isImplemented: true,
    permissions: ["read", "analytics"],
    version: "2.0.0", // Updated version with real AI
    execute: async (params, context) => {
        const startTime = Date.now();
        try {
            const validatedParams = debugAIOutputSchema.parse(params);
            const { aiOutput, expectedBehavior, context: debugContext, outputType, includeFixSuggestions, } = validatedParams;
            // Get AI provider for real output analysis
            const providerName = await getBestProvider();
            const provider = await AIProviderFactory.createProvider(providerName);
            if (!provider) {
                throw new Error(`Failed to create AI provider: ${providerName}`);
            }
            // Create structured prompt for AI output debugging
            const prompt = `Analyze this AI-generated ${outputType} output for issues and improvements:

AI Output to Debug:
\`\`\`
${aiOutput}
\`\`\`

Expected Behavior:
${expectedBehavior}

Context: ${debugContext || "None provided"}
Output Type: ${outputType}
Include Fix Suggestions: ${includeFixSuggestions}

Analyze the output for:
1. Quality issues (completeness, accuracy, formatting)
2. Technical problems (syntax errors, logical flaws)
3. Content issues (relevance, clarity, consistency)
4. Improvement opportunities

Return ONLY a valid JSON object with this exact structure:
{
  "issues": [
    {
      "type": "issue-category",
      "severity": "low|medium|high",
      "description": "detailed description of the issue",
      "location": "where in output this occurs"
    }
  ],
  "suggestions": ["actionable improvement suggestion 1", "suggestion 2"],
  "possibleCauses": ["potential cause 1", "potential cause 2"],
  "fixedOutput": ${includeFixSuggestions ? '"corrected version if possible"' : "null"}
}

Provide thorough, actionable analysis focused on improving AI output quality.`;
            const result = await provider.generate({
                prompt: prompt,
                maxTokens: DEFAULT_MAX_TOKENS,
                temperature: 0.4, // Moderate temperature for analytical thinking
            });
            if (!result || !result.content) {
                throw new Error("AI provider returned no result for output debugging.");
            }
            // Parse AI response
            const aiResponse = JSON.parse(result.content);
            const executionTime = Date.now() - startTime;
            const responseData = {
                issues: aiResponse.issues || [],
                suggestions: aiResponse.suggestions || [
                    "Consider refining the prompt for clearer instructions",
                ],
                possibleCauses: aiResponse.possibleCauses || [
                    "Prompt clarity",
                    "Model limitations",
                ],
                fixedOutput: aiResponse.fixedOutput || undefined,
            };
            return {
                success: true,
                data: {
                    ...responseData,
                    originalOutput: aiOutput,
                    expectedBehavior,
                    outputType,
                    analysisContext: debugContext,
                    generatedAt: new Date().toISOString(),
                    aiProvider: providerName,
                },
                usage: {
                    ...result.usage,
                    executionTime,
                    provider: providerName,
                    model: "ai-output-debugger",
                },
                metadata: {
                    toolName: "debug-ai-output",
                    serverId: "neurolink-ai-core",
                    sessionId: context.sessionId,
                    timestamp: Date.now(),
                    executionTime,
                },
            };
        }
        catch (error) {
            const executionTime = Date.now() - startTime;
            const errorMessage = error instanceof Error ? error.message : String(error);
            return {
                success: false,
                error: errorMessage,
                metadata: {
                    toolName: "debug-ai-output",
                    serverId: "neurolink-ai-core",
                    sessionId: context.sessionId,
                    timestamp: Date.now(),
                    executionTime,
                },
            };
        }
    },
};
// Helper functions
function _extractFunctionName(code) {
    const match = code.match(/function\s+(\w+)|const\s+(\w+)\s*=|(\w+)\s*\(/);
    return match
        ? match[1] || match[2] || match[3] || "processData"
        : "processData";
}
function _simulateRefactoring(code, objectives, _styleGuide) {
    // Simulate basic refactoring
    let refactored = code;
    if (objectives.includes("readability")) {
        refactored = refactored.replace(/([a-z])([A-Z])/g, "$1 $2");
    }
    if (objectives.includes("dry-principle")) {
        refactored = `// Extracted common functionality\nconst CONSTANTS = { MAX_RETRIES: 3, TIMEOUT: 5000 };\n\n${refactored}`;
    }
    return refactored;
}
// REMOVED: Tool exports disabled to prevent provider conflicts
// const aiWorkflowTools = [
//   generateTestCasesTool,
//   refactorCodeTool,
//   generateDocumentationTool,
//   debugAIOutputTool,
// ];
// REMOVED: Schema exports disabled
// const workflowToolSchemas = {
//   "generate-test-cases": generateTestCasesSchema,
//   "refactor-code": refactorCodeSchema,
//   "generate-documentation": generateDocumentationSchema,
//   "debug-ai-output": debugAIOutputSchema,
// };
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