wip v26

Author: geraldarthurdavis

packages/chatgptapp/src/__tests__/tools.test.ts

@@ -142,16 +142,16 @@ This product delivers voice-first social conversations for builders.
 
   it('improve_developing_behavior refreshes baseline via digest when requested', async () => {
     const result = await runTool<{
-      latest_behavior: string;
+      latestBehavior: string;
       metadata: { digestUsed?: boolean };
     }>('improve_developing_behavior', {
-      improvement_betterment: 'Always cite file paths with line numbers.',
+      behaviorImprovement: 'Always cite file paths with line numbers.',
       regenerateFromDigest: true,
     });
     expect(generateDigestMock).toHaveBeenCalled();
     expect(result.metadata.digestUsed).toBe(true);
-    expect(result.latest_behavior).toContain('Confirm Supabase credentials before coding.');
-    expect(result.latest_behavior).toContain('Always cite file paths');
+    expect(result.latestBehavior).toContain('Confirm Supabase credentials before coding.');
+    expect(result.latestBehavior).toContain('Always cite file paths');
   });
 
   it('use_vercel_read_external_mcp handles list_deployments', async () => {
@@ -290,17 +290,17 @@ This product delivers voice-first social conversations for builders.
   it('improve_developing_behavior reports digest errors and uses template baseline', async () => {
     generateDigestMock.mockRejectedValueOnce(new Error('agents digest unavailable'));
     const result = await runTool<{
-      latest_behavior: string;
+      latestBehavior: string;
       metadata: { digestUsed?: boolean; digestError?: string };
     }>('improve_developing_behavior', {
-      improvement_betterment: 'Record when successors need live narration.',
+      behaviorImprovement: 'Record when successors need live narration.',
       regenerateFromDigest: true,
     });
 
     expect(result.metadata.digestUsed).toBe(false);
     expect(result.metadata.digestError).toBe('agents digest unavailable');
-    expect(result.latest_behavior).toContain('### Behavior Evolution');
-    expect(result.latest_behavior).toContain('Record when successors need live narration.');
-    expect(result.latest_behavior).toContain('# AGENTS\' INSTRUCTIONS:\n\n- []');
+    expect(result.latestBehavior).toContain('### Behavior Improvement');
+    expect(result.latestBehavior).toContain('Record when successors need live narration.');
+    expect(result.latestBehavior).toContain('# AGENTS\' INSTRUCTIONS:\n\n- []');
   });
 });

packages/chatgptapp/src/__tests__/yapperFlow.test.ts

@@ -217,14 +217,14 @@ This product delivers voice-first social conversations for builders.
 
     // Step 11: Capture agent learnings, regenerating baseline
     const agentsUpdate = await runTool<{
-      latest_behavior: string;
+      latestBehavior: string;
       metadata: { digestUsed?: boolean };
     }>('improve_developing_behavior', {
-      improvement_betterment: 'Always cite file paths with numbers when summarising code.',
+      behaviorImprovement: 'Always cite file paths with numbers when summarising code.',
       regenerateFromDigest: true,
     });
     expect(generateDigestMock).toHaveBeenCalledTimes(2);
     expect(agentsUpdate.metadata.digestUsed).toBe(true);
-    expect(agentsUpdate.latest_behavior).toContain('Always cite file paths');
+    expect(agentsUpdate.latestBehavior).toContain('Always cite file paths');
   });
 });

packages/chatgptapp/src/tools.ts

@@ -803,14 +803,14 @@ const WRITE_CODE_CHANGES_SCHEMA = {
 };
 
 const IMPROVE_BEHAVIOR_VALIDATOR = z.object({
-  improvement_betterment: z.string().optional().describe('Notes about desired agent behavior changes'),
+  behaviorImprovement: z.string().optional().describe('Notes about desired development behavior changes'),
   currentAgentsMd: z.string().optional().describe('Optional current AGENTS.md for reference'),
   regenerateFromDigest: z.boolean().optional().describe('Regenerate the baseline AGENTS.md from digest before applying updates')
 }).strict();
 
 async function executeImproveDevelopingBehavior(args: z.infer<typeof IMPROVE_BEHAVIOR_VALIDATOR>) {
-  const focus = args.improvement_betterment?.slice(0, 120) || 'general';
-  const update = ['### Behavior Evolution', args.improvement_betterment ?? 'Capture new behaviors next session.'].join('\n');
+  const focus = args.behaviorImprovement?.slice(0, 120) || 'general';
+  const update = ['### Behavior Improvement', args.behaviorImprovement ?? 'Capture new behaviors next session.'].join('\n');
 
   let baseDocument = args.currentAgentsMd && args.currentAgentsMd.trim().length > 0
     ? args.currentAgentsMd.trim()
@@ -855,8 +855,8 @@ async function executeImproveDevelopingBehavior(args: z.infer<typeof IMPROVE_BEH
       ? `Digest refresh unavailable (${digestError}); using provided AGENTS.md context.`
       : 'Appended behaviour notes to the provided AGENTS.md context.';
 
-  const behaviorInsights = args.improvement_betterment
-    ? args.improvement_betterment
+  const behaviorInsights = args.behaviorImprovement
+    ? args.behaviorImprovement
         .split(/\r?\n/)
         .map((line) => line.trim())
         .filter(Boolean)
@@ -867,9 +867,9 @@ async function executeImproveDevelopingBehavior(args: z.infer<typeof IMPROVE_BEH
   });
 
   return {
-    thennnowevolution: update,
-    concretelatestgreatestapproach: latestBehavior,
-    latest_behavior: latestBehavior,
+    behaviorDelta: update,
+    latestBehaviorDocument: latestBehavior,
+    latestBehavior: latestBehavior,
     metadata: {
       focus,
       created,
@@ -886,9 +886,9 @@ const IMPROVE_BEHAVIOR_SCHEMA = {
   type: 'object',
   additionalProperties: false,
   properties: {
-    improvement_betterment: {
+    behaviorImprovement: {
       type: 'string',
-      description: 'Notes about desired agent behavior changes'
+      description: 'Notes about desired development behavior changes'
     },
     currentAgentsMd: {
       type: 'string',

packages/executions-mcp/src/mcp-server/src/docs/mcp-spec-generator.ts

@@ -97,7 +97,7 @@ export class MCPSpecificationGenerator {
       serverInfo: {
         name: 'bitcode-market-infrastructure',
         version: '1.0.0',
-        description: 'Engineering intelligence platform exposing comprehensive capabilities through MCP',
+        description: 'Technical knowledge exchange platform exposing comprehensive capabilities through MCP',
         capabilities: [
           'Pipeline Management', 'Advanced Intelligence', 'Enterprise Integration',
           'LSP Integration', 'Observability', 'Cross-Repository Learning'
@@ -287,7 +287,7 @@ export class MCPSpecificationGenerator {
     if (description.includes('refactor')) useCases.push('Code Refactoring');
     if (description.includes('analytics')) useCases.push('Business Intelligence');
 
-    return useCases.length > 0 ? useCases : ['General Engineering'];
+    return useCases.length > 0 ? useCases : ['General Technical Work'];
   }
 
   /**
@@ -375,7 +375,7 @@ export class MCPSpecificationGenerator {
       'Analysis': 'Code analysis and repository intelligence'
     };
 
-    return descriptions[category] || 'Engineering intelligence tools';
+    return descriptions[category] || 'Technical knowledge tools';
   }
 
   /**

packages/executions-mcp/src/mcp-server/src/docs/openapi-generator.ts

@@ -29,7 +29,7 @@ export function generateOpenAPISpec(): OpenAPIV3.Document {
       description: `
 # Bitcode MCP Server API
 
-The Model Context Protocol (MCP) server exposing Bitcode’s engineering intelligence via standardized tools, resources, and prompts.
+The Model Context Protocol (MCP) server exposing Bitcode’s technical knowledge exchange via standardized tools, resources, and prompts.
 
 ## Features
 

packages/executions-mcp/src/mcp-server/src/prompts/analysis-prompts.ts

@@ -2,7 +2,7 @@
  * Bitcode MCP Analysis Prompts
  * 
  * Specialized prompts for technical analysis, code investigation,
- * and engineering intelligence gathering.
+ * and technical knowledge gathering.
  */
 
 import { z } from 'zod';

packages/executions-mcp/src/mcp-server/src/resources/intelligence-resources.ts

@@ -2,7 +2,7 @@
  * Bitcode MCP Intelligence Resources - ORM Integration
  * 
  * Updated to use ORM models for all database operations.
- * Provides AI-generated engineering intelligence through MCP resources.
+ * Provides AI-generated technical knowledge through MCP resources.
  * 
  * @doc-code
  * type: resources
@@ -87,7 +87,7 @@ function parseQueryParams(uri: string): Record<string, any> {
 }
 
 /**
- * Synthesize engineering intelligence
+ * Synthesize technical knowledge
  */
 async function synthesizeIntelligence(
   context: MCPAuthContext,
@@ -97,7 +97,7 @@ async function synthesizeIntelligence(
   const pipelineRuns = new PipelineExecutionsModel(supabase);
 
   try {
-    logger.info('Synthesizing engineering intelligence', {
+    logger.info('Synthesizing technical knowledge', {
       scope: options.scope,
       timeframe: options.timeframe,
       userId: context.userId
@@ -668,8 +668,8 @@ export function registerIntelligenceResources(): MCPResource[] {
   return [
     {
       uri: 'bitcode://resources/intelligence/synthesis',
-      name: 'Engineering Intelligence Synthesis',
-      description: 'AI-powered synthesis of engineering insights, trends, and recommendations',
+      name: 'Technical Knowledge Synthesis',
+      description: 'AI-powered synthesis of technical insights, trends, and recommendations',
       mimeType: 'application/json',
 
       read: async (uri: string, context: MCPAuthContext) => {

packages/executions-mcp/src/mcp-server/src/tools/analysis-tools.ts

@@ -2,7 +2,7 @@
  * Bitcode MCP Analysis Tools
  * 
  * Advanced AI-powered analysis tools for repository intelligence,
- * architectural insights, and engineering intelligence synthesis.
+ * architectural insights, and technical knowledge synthesis.
  */
 
 import { z } from 'zod';
@@ -418,17 +418,17 @@ Generates actionable insights with confidence scoring and remediation guidance.`
 
     {
       name: 'bitcode://analysis/intelligence/synthesize',
-      description: `Synthesize engineering intelligence across repositories and time periods.
+      description: `Synthesize technical knowledge across repositories and time periods.
 
 AI-powered intelligence synthesis providing:
 • Cross-repository pattern identification
-• Engineering productivity trend analysis
+• Technical productivity trend analysis
 • Quality and security posture evolution
 • Technology adoption and migration insights
 • Team performance and collaboration patterns
 • Predictive insights for technical decisions
 
-Generates strategic insights for engineering leadership with confidence-scored recommendations.`,
+Generates strategic insights for technical leadership with confidence-scored recommendations.`,
 
       inputSchema: IntelligenceSynthesisSchema,
 

packages/executions-mcp/src/mcp-server/src/tools/intelligence-tools.ts

@@ -22,7 +22,7 @@ interface MCPTool {
 
 /**
  * EFFECTIVENESS TRACKING INTELLIGENCE
- * Revolutionary real-time quality measurement and learning system
+ * Real-time quality measurement and learning system
  */
 const effectivenessTrackingToolSchema = z.object({
   operation: z.enum(['measure', 'predict', 'learn', 'optimize'])
@@ -577,7 +577,7 @@ export function registerIntelligenceTools(): MCPTool[] {
   return [
     {
       name: 'bitcode://intelligence/effectiveness/track',
-      description: `Revolutionary effectiveness tracking system with real-time quality measurement.
+      description: `Effectiveness tracking system with real-time quality measurement.
 
 This system provides unprecedented insight into code change effectiveness:
 • Real-time before/after quality measurement
@@ -610,7 +610,7 @@ Enables knowledge transfer and standardization across your entire codebase ecosy
 
     {
       name: 'bitcode://intelligence/research/advanced',
-      description: `Revolutionary multi-provider web research with URL intelligence and synthesis.
+      description: `Multi-provider web research with URL intelligence and synthesis.
 
 Multi-wave research orchestration across diverse sources:
 • GitHub, Stack Overflow, academic papers, documentation sites
@@ -645,7 +645,7 @@ Advanced multimodal intelligence processing:
 • Figma design analysis with implementation guidance
 • Cross-modal synthesis for unified understanding
 
-Transforms any media type into actionable engineering intelligence.`,
+Transforms any media type into actionable technical knowledge evidence.`,
 
       inputSchema: multimodalProcessingToolSchema,
       execute: async (args, context) => {

packages/executions-mcp/src/mcp-server/src/tools/observability-tools.ts

@@ -171,7 +171,7 @@ const distributedTracingSchema = z.object({
 
 /**
  * BUSINESS INTELLIGENCE & ANALYTICS
- * Engineering metrics, KPIs, and strategic insights
+ * Technical metrics, KPIs, and strategic insights
  */
 const businessIntelligenceSchema = z.object({
   operation: z.enum([
@@ -596,7 +596,7 @@ Enables deep performance understanding in distributed systems.`,
       description: `Business intelligence platform for engineering metrics and strategic insights.
 
 Strategic analytics capabilities:
-• Engineering productivity metrics with team comparisons
+• Technical productivity metrics with team comparisons
 • ROI calculation for engineering investments
 • Technical debt analysis with cost implications
 • Velocity trends with predictive forecasting
@@ -647,4 +647,4 @@ Transforms logs into actionable intelligence for operational excellence.`,
       }
     }
   ];
-}
+}