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Universal AI Development Platform with working MCP integration, multi-provider support, and professional CLI. Built-in tools operational, 58+ external MCP servers discoverable. Connect to filesystem, GitHub, database operations, and more. Build, test, and
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JavaScript
/**
* 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"),
});
/**
* 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: Math.floor(DEFAULT_MAX_TOKENS * 1.2),
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: Math.floor(DEFAULT_MAX_TOKENS * 1.2),
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,
// };