Completes the For-Claude-Web bundle licence migration. All 16 in-scope files (Maintenance_Guide done in5c386d0d+ 15 here) now reference EUPL-1.2. CLAUDE_WEB_BRIEF.md:250 "MIT or Apache license" preserved per plan — historical project context, not an active claim. 31 token swaps applied via throwaway script + 2 full-block rewrites: Token swaps (longest-first pattern order for atomicity): #1. Full Apache preamble paragraph (3 paragraphs, header + URL + AS-IS body) -> EUPL-1.2 equivalent. Normalises "License" -> "Licence" across the body in one pass so the paragraph is internally consistent (British spelling per EUPL official style). Applied to 12 files. #2. "Apache License, Version 2.0, January 2004" -> "European Union Public Licence, Version 1.2" (2 files). #3. "Apache License, Version 2.0 (the \"License\")" variant -> EUPL variant (covered by #1; fallback for non-preamble contexts). #4. "Apache License, Version 2.0" -> "European Union Public Licence, Version 1.2 (EUPL-1.2)" (non-preamble fallback). #5. "Apache License 2.0" -> "European Union Public Licence, v. 1.2 (EUPL-1.2)" (1 file, 27027-incident "**License:** Apache License 2.0"). #6. "Apache 2.0 license" -> "EUPL-1.2 licence" (7 files x 2 each = 14 hits; all in "Additional Terms" boilerplate). #7. "Apache 2.0 License" -> "EUPL-1.2 License" (1 file, roadmap "**Apache 2.0 License**"). #8. "http://www.apache.org/licenses/LICENSE-2.0" -> EUPL URL (covered by #1). #9. "Apache 2.0" bare -> "EUPL-1.2" (1 file, claude-code-framework-enforcement "**License**: Apache 2.0"). Full-block rewrites (technical-architecture.md, implementation-guide.md): Both files embedded the ~55-line Apache TERMS AND CONDITIONS text verbatim (lines 648-703 / 893-948 pre-rewrite). Simple token-swap would have produced mislabelled "EUPL-1.2" header with Apache-specific TERMS body below. Replaced entire block with: **Full Licence Text:** For the full EUPL-1.2 licence text, see: https://interoperable-europe.ec.europa.eu/collection/eupl/eupl-text-eupl-12 The EUPL-1.2 is available in 23 official EU-language versions at the same source. Matches Phase A precedent (root LICENSE filec85f310freferences the canonical EUPL source rather than embedding verbatim). Vendor-policy note (intentionally DEFERRED per plan): "**GitHub:** https://github.com/AgenticGovernance/tractatus-framework" references in technical-architecture L719 and similar elsewhere are GitHub->Codeberg cleanup, tracked as a separate broader sweep. Not bundled into this licence commit. Commit 4/5 in the revised sequence. Plan: community repo docs/plans/PLAN_TRACTATUS_OUT_OF_SCOPE_HYGIENE_LICENCE_20260420.md Phase A precedent:c85f310f(root LICENSE + README + source headers) Phase B precedent:d600f6ed(source-file header sweep) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
902 lines
22 KiB
Markdown
902 lines
22 KiB
Markdown
---
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title: Implementation Guide
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slug: implementation-guide
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quadrant: OPERATIONAL
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persistence: HIGH
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version: 1.0
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type: framework
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author: SyDigital Ltd
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---
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# Tractatus Framework Implementation Guide
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## Quick Start
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### Prerequisites
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- Node.js 18+
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- MongoDB 7+
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- npm or yarn
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### Installation
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```bash
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npm install tractatus-framework
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# or
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yarn add tractatus-framework
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```
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### Basic Setup
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```javascript
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const {
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InstructionPersistenceClassifier,
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CrossReferenceValidator,
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BoundaryEnforcer,
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ContextPressureMonitor,
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MetacognitiveVerifier,
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PluralisticDeliberationOrchestrator
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} = require('tractatus-framework');
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// Initialize services
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const classifier = new InstructionPersistenceClassifier();
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const validator = new CrossReferenceValidator();
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const enforcer = new BoundaryEnforcer();
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const monitor = new ContextPressureMonitor();
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const verifier = new MetacognitiveVerifier();
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const deliberator = new PluralisticDeliberationOrchestrator();
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```
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---
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## Integration Patterns
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### Pattern 1: LLM Development Assistant
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**Use Case**: Prevent AI coding assistants from forgetting instructions or making values decisions.
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**Implementation**:
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```javascript
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// 1. Classify user instructions
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app.on('user-message', async (message) => {
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const classification = classifier.classify({
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text: message.text,
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source: 'user'
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});
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if (classification.persistence === 'HIGH' &&
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classification.explicitness >= 0.6) {
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await instructionDB.store(classification);
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}
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});
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// 2. Validate AI actions before execution
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app.on('ai-action', async (action) => {
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// Cross-reference check
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const validation = await validator.validate(
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action,
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{ explicit_instructions: await instructionDB.getActive() }
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);
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if (validation.status === 'REJECTED') {
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return { error: validation.reason, blocked: true };
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}
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// Boundary check
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const boundary = enforcer.enforce(action);
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if (!boundary.allowed) {
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return { error: boundary.reason, requires_human: true };
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}
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// Metacognitive verification
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const verification = verifier.verify(
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action,
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action.reasoning,
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{ explicit_instructions: await instructionDB.getActive() }
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);
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if (verification.decision === 'BLOCKED') {
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return { error: 'Low confidence', blocked: true };
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}
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// Execute action
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return executeAction(action);
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});
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// 3. Monitor session pressure
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app.on('session-update', async (session) => {
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const pressure = monitor.analyzePressure({
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token_usage: session.tokens / session.max_tokens,
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conversation_length: session.messages.length,
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tasks_active: session.tasks.length,
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errors_recent: session.errors.length
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});
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if (pressure.pressureName === 'CRITICAL' ||
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pressure.pressureName === 'DANGEROUS') {
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await createSessionHandoff(session);
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notifyUser('Session quality degraded, handoff created');
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}
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});
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```
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---
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### Pattern 2: Content Moderation System
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**Use Case**: AI-powered content moderation with human oversight for edge cases.
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**Implementation**:
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```javascript
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async function moderateContent(content) {
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// AI analyzes content
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const analysis = await aiAnalyze(content);
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// Boundary check: Is this a values decision?
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const boundary = enforcer.enforce({
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type: 'content_moderation',
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action: analysis.recommended_action,
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domain: 'values' // Content moderation involves values
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});
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if (!boundary.allowed) {
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// Queue for human review
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await moderationQueue.add({
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content,
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ai_analysis: analysis,
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reason: boundary.reason,
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status: 'pending_human_review'
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});
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return {
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decision: 'HUMAN_REVIEW_REQUIRED',
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reason: 'Content moderation involves values judgments'
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};
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}
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// For clear-cut cases (spam, obvious violations)
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if (analysis.confidence > 0.95) {
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return {
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decision: analysis.recommended_action,
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automated: true
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};
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}
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// Queue uncertain cases
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await moderationQueue.add({
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content,
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ai_analysis: analysis,
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status: 'pending_review'
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});
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return { decision: 'QUEUED_FOR_REVIEW' };
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}
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```
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---
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### Pattern 3: Configuration Management
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**Use Case**: Prevent AI from changing critical configuration without human approval.
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**Implementation**:
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```javascript
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async function updateConfig(key, value, proposedBy) {
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// Classify the configuration change
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const classification = classifier.classify({
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text: `Set ${key} to ${value}`,
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source: proposedBy
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});
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// Check if this conflicts with existing instructions
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const validation = validator.validate(
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{ type: 'config_change', parameters: { [key]: value } },
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{ explicit_instructions: await instructionDB.getActive() }
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);
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if (validation.status === 'REJECTED') {
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throw new Error(
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`Config change conflicts with instruction: ${validation.instruction_violated}`
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);
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}
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// Boundary check: Is this a critical system setting?
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if (classification.quadrant === 'SYSTEM' &&
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classification.persistence === 'HIGH') {
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const boundary = enforcer.enforce({
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type: 'system_config_change',
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domain: 'system_critical'
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});
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if (!boundary.allowed) {
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await approvalQueue.add({
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type: 'config_change',
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key,
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value,
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current_value: config[key],
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requires_approval: true
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});
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return { status: 'PENDING_APPROVAL' };
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}
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}
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// Apply change
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config[key] = value;
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await saveConfig();
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// Store as instruction if persistence is HIGH
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if (classification.persistence === 'HIGH') {
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await instructionDB.store({
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...classification,
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parameters: { [key]: value }
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});
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}
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return { status: 'APPLIED' };
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}
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```
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---
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## Service-Specific Integration
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### InstructionPersistenceClassifier
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**When to Use:**
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- User provides explicit instructions
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- Configuration changes
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- Policy updates
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- Procedural guidelines
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**Integration:**
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```javascript
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// Classify instruction
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const result = classifier.classify({
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text: "Always use camelCase for JavaScript variables",
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source: "user"
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});
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// Result structure
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{
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quadrant: "OPERATIONAL",
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persistence: "MEDIUM",
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temporal_scope: "PROJECT",
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verification_required: "REQUIRED",
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explicitness: 0.78,
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reasoning: "Code style convention for project duration"
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}
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// Store if explicitness >= threshold
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if (result.explicitness >= 0.6) {
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await instructionDB.store({
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id: generateId(),
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text: result.text,
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...result,
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timestamp: new Date(),
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active: true
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});
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}
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```
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---
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### CrossReferenceValidator
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**When to Use:**
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- Before executing any AI-proposed action
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- Before code generation
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- Before configuration changes
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- Before policy updates
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**Integration:**
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```javascript
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// Validate proposed action
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const validation = await validator.validate(
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{
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type: 'database_connect',
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parameters: { port: 27017, host: 'localhost' }
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},
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{
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explicit_instructions: await instructionDB.getActive()
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}
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);
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// Handle validation result
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switch (validation.status) {
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case 'APPROVED':
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await executeAction();
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break;
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case 'WARNING':
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console.warn(validation.reason);
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await executeAction(); // Proceed with caution
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break;
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case 'REJECTED':
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throw new Error(
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`Action blocked: ${validation.reason}\n` +
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`Violates instruction: ${validation.instruction_violated}`
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);
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}
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```
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---
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### BoundaryEnforcer
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**When to Use:**
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- Before any decision that might involve values
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- Before user-facing policy changes
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- Before data collection/privacy changes
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- Before irreversible operations
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**Integration:**
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```javascript
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// Check if decision crosses boundary
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const boundary = enforcer.enforce(
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{
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type: 'privacy_policy_update',
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action: 'enable_analytics'
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},
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{
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domain: 'values' // Privacy vs. analytics is a values trade-off
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}
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);
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if (!boundary.allowed) {
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// Cannot automate this decision
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return {
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error: boundary.reason,
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alternatives: boundary.ai_can_provide,
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requires_human_decision: true
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};
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}
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// If allowed, proceed
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await executeAction();
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```
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---
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### ContextPressureMonitor
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**When to Use:**
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- Continuously throughout session
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- After errors
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- Before complex operations
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- At regular intervals (e.g., every 10 messages)
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**Integration:**
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```javascript
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// Monitor pressure continuously
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setInterval(async () => {
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const pressure = monitor.analyzePressure({
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token_usage: session.tokens / session.max_tokens,
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conversation_length: session.messages.length,
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tasks_active: activeTasks.length,
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errors_recent: recentErrors.length,
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instructions_active: (await instructionDB.getActive()).length
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});
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// Update UI
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updatePressureIndicator(pressure.pressureName, pressure.pressure);
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// Take action based on pressure
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if (pressure.pressureName === 'HIGH') {
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showWarning('Session quality degrading, consider break');
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}
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if (pressure.pressureName === 'CRITICAL') {
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await createHandoff(session);
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showNotification('Session handoff created, please start fresh');
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}
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if (pressure.pressureName === 'DANGEROUS') {
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blockNewOperations();
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forceHandoff(session);
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}
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}, 60000); // Check every minute
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```
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---
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### MetacognitiveVerifier
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**When to Use:**
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- Before complex operations (multi-file refactors)
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- Before security changes
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- Before database schema changes
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- Before major architectural decisions
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**Integration:**
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```javascript
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// Verify complex operation
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const verification = verifier.verify(
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{
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type: 'refactor',
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files: ['auth.js', 'database.js', 'api.js'],
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scope: 'authentication_system'
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},
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{
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reasoning: [
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'Current JWT implementation has security issues',
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'OAuth2 is industry standard',
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'Users expect social login',
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'Will modify 3 files'
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]
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},
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{
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explicit_instructions: await instructionDB.getActive(),
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pressure_level: currentPressure
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}
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);
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// Handle verification result
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if (verification.confidence < 0.4) {
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return {
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error: 'Confidence too low',
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concerns: verification.checks.concerns,
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blocked: true
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};
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}
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if (verification.decision === 'REQUIRE_REVIEW') {
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await reviewQueue.add({
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action,
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verification,
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requires_human_review: true
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});
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return { status: 'QUEUED_FOR_REVIEW' };
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}
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if (verification.decision === 'PROCEED_WITH_CAUTION') {
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console.warn('Proceeding with increased verification');
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// Enable extra checks
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}
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// Proceed
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await executeAction();
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```
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---
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### PluralisticDeliberationOrchestrator
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**When to Use:**
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- When BoundaryEnforcer flags a values conflict
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- Privacy vs. safety trade-offs
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- Individual rights vs. collective welfare tensions
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- Cultural values conflicts
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- Policy decisions affecting diverse communities
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**Integration:**
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```javascript
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// Trigger deliberation when values conflict detected
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async function handleValuesDecision(decision) {
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// First, BoundaryEnforcer blocks the decision
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const boundary = enforcer.enforce(decision);
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if (!boundary.allowed && boundary.reason.includes('values')) {
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// Initiate pluralistic deliberation
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const deliberation = await deliberator.orchestrate({
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decision: decision,
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context: {
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stakeholders: ['privacy_advocates', 'safety_team', 'legal', 'affected_users'],
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moral_frameworks: ['deontological', 'consequentialist', 'care_ethics'],
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urgency: 'IMPORTANT' // CRITICAL, URGENT, IMPORTANT, ROUTINE
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}
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});
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// Structure returned:
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// {
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// status: 'REQUIRES_HUMAN_APPROVAL',
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// stakeholder_list: [...],
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// deliberation_structure: {
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// rounds: 3,
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// values_in_tension: ['privacy', 'harm_prevention'],
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// frameworks: ['deontological', 'consequentialist']
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// },
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// outcome_template: {
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// decision: null,
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// values_prioritized: [],
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// values_deprioritized: [],
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// moral_remainder: null,
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// dissenting_views: [],
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// review_date: null
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// },
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// precedent_applicability: {
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// narrow: 'user_data_disclosure_imminent_threat',
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// broad: 'privacy_vs_safety_tradeoffs'
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// }
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// }
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// AI facilitates, humans decide (mandatory human approval)
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await approvalQueue.add({
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type: 'pluralistic_deliberation',
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decision: decision,
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deliberation_plan: deliberation,
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requires_human_approval: true,
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stakeholder_approval_required: true // Must approve stakeholder list
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});
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return {
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status: 'DELIBERATION_INITIATED',
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message: 'Values conflict detected. Pluralistic deliberation process started.',
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stakeholders_to_convene: deliberation.stakeholder_list
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};
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}
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return { status: 'NO_DELIBERATION_NEEDED' };
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}
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// After human-led deliberation, store outcome as precedent
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async function storeDeliberationOutcome(outcome) {
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await deliberator.storePrecedent({
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decision: outcome.decision,
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values_prioritized: outcome.values_prioritized,
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values_deprioritized: outcome.values_deprioritized,
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moral_remainder: outcome.moral_remainder,
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dissenting_views: outcome.dissenting_views,
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review_date: outcome.review_date,
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applicability: {
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narrow: outcome.narrow_scope,
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broad: outcome.broad_scope
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},
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binding: false // Precedents are informative, not binding
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});
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return { status: 'PRECEDENT_STORED' };
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}
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```
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**Key Principles:**
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- **Foundational Pluralism**: No universal value hierarchy (privacy > safety or safety > privacy)
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- **Legitimate Disagreement**: Valid outcome when values genuinely incommensurable
|
|
- **Human-in-the-Loop**: AI facilitates deliberation structure, humans make decisions
|
|
- **Non-Hierarchical**: No automatic ranking of moral frameworks
|
|
- **Provisional Decisions**: All values decisions reviewable when context changes
|
|
- **Moral Remainder Documentation**: Record what's lost in trade-offs
|
|
|
|
---
|
|
|
|
## Configuration
|
|
|
|
### Instruction Storage
|
|
|
|
**Database Schema:**
|
|
|
|
```javascript
|
|
{
|
|
id: String,
|
|
text: String,
|
|
timestamp: Date,
|
|
quadrant: String, // STRATEGIC, OPERATIONAL, TACTICAL, SYSTEM, STOCHASTIC
|
|
persistence: String, // HIGH, MEDIUM, LOW, VARIABLE
|
|
temporal_scope: String, // PERMANENT, PROJECT, PHASE, SESSION, TASK
|
|
verification_required: String, // MANDATORY, REQUIRED, OPTIONAL, NONE
|
|
explicitness: Number, // 0.0 - 1.0
|
|
source: String, // user, system, inferred
|
|
session_id: String,
|
|
parameters: Object,
|
|
active: Boolean,
|
|
notes: String
|
|
}
|
|
```
|
|
|
|
**Storage Options:**
|
|
|
|
```javascript
|
|
// Option 1: JSON file (simple)
|
|
const fs = require('fs');
|
|
const instructionDB = {
|
|
async getActive() {
|
|
const data = await fs.readFile('.claude/instruction-history.json');
|
|
return JSON.parse(data).instructions.filter(i => i.active);
|
|
},
|
|
async store(instruction) {
|
|
const data = JSON.parse(await fs.readFile('.claude/instruction-history.json'));
|
|
data.instructions.push(instruction);
|
|
await fs.writeFile('.claude/instruction-history.json', JSON.stringify(data, null, 2));
|
|
}
|
|
};
|
|
|
|
// Option 2: MongoDB
|
|
const instructionDB = {
|
|
async getActive() {
|
|
return await db.collection('instructions').find({ active: true }).toArray();
|
|
},
|
|
async store(instruction) {
|
|
await db.collection('instructions').insertOne(instruction);
|
|
}
|
|
};
|
|
|
|
// Option 3: Redis (for distributed systems)
|
|
const instructionDB = {
|
|
async getActive() {
|
|
const keys = await redis.keys('instruction:*:active');
|
|
return await Promise.all(keys.map(k => redis.get(k).then(JSON.parse)));
|
|
},
|
|
async store(instruction) {
|
|
await redis.set(
|
|
`instruction:${instruction.id}:active`,
|
|
JSON.stringify(instruction)
|
|
);
|
|
}
|
|
};
|
|
```
|
|
|
|
---
|
|
|
|
## Best Practices
|
|
|
|
### 1. Start Simple
|
|
|
|
Begin with just InstructionPersistenceClassifier and CrossReferenceValidator:
|
|
|
|
```javascript
|
|
// Minimal implementation
|
|
const { InstructionPersistenceClassifier, CrossReferenceValidator } = require('tractatus-framework');
|
|
|
|
const classifier = new InstructionPersistenceClassifier();
|
|
const validator = new CrossReferenceValidator();
|
|
const instructions = [];
|
|
|
|
// Classify and store
|
|
app.on('user-instruction', (text) => {
|
|
const classified = classifier.classify({ text, source: 'user' });
|
|
if (classified.explicitness >= 0.6) {
|
|
instructions.push(classified);
|
|
}
|
|
});
|
|
|
|
// Validate before actions
|
|
app.on('ai-action', (action) => {
|
|
const validation = validator.validate(action, { explicit_instructions: instructions });
|
|
if (validation.status === 'REJECTED') {
|
|
throw new Error(validation.reason);
|
|
}
|
|
});
|
|
```
|
|
|
|
### 2. Add Services Incrementally
|
|
|
|
Once comfortable:
|
|
1. Add BoundaryEnforcer for values-sensitive domains
|
|
2. Add ContextPressureMonitor for long sessions
|
|
3. Add MetacognitiveVerifier for complex operations
|
|
4. Add PluralisticDeliberationOrchestrator for multi-stakeholder values conflicts
|
|
|
|
### 3. Tune Thresholds
|
|
|
|
Adjust thresholds based on your use case:
|
|
|
|
```javascript
|
|
const config = {
|
|
classifier: {
|
|
min_explicitness: 0.6, // Lower = more instructions stored
|
|
auto_store_threshold: 0.75 // Higher = only very explicit instructions
|
|
},
|
|
validator: {
|
|
conflict_tolerance: 0.8 // How similar before flagging conflict
|
|
},
|
|
pressure: {
|
|
elevated: 0.30, // Adjust based on observed session quality
|
|
high: 0.50,
|
|
critical: 0.70
|
|
},
|
|
verifier: {
|
|
min_confidence: 0.60 // Minimum confidence to proceed
|
|
}
|
|
};
|
|
```
|
|
|
|
### 4. Log Everything
|
|
|
|
Comprehensive logging enables debugging and audit trails:
|
|
|
|
```javascript
|
|
const logger = require('winston');
|
|
|
|
// Log all governance decisions
|
|
validator.on('validation', (result) => {
|
|
logger.info('Validation:', result);
|
|
});
|
|
|
|
enforcer.on('boundary-check', (result) => {
|
|
logger.warn('Boundary check:', result);
|
|
});
|
|
|
|
monitor.on('pressure-change', (pressure) => {
|
|
logger.info('Pressure:', pressure);
|
|
});
|
|
```
|
|
|
|
### 5. Human-in-the-Loop UI
|
|
|
|
Provide clear UI for human oversight:
|
|
|
|
```javascript
|
|
// Example: Approval queue UI
|
|
app.get('/admin/approvals', async (req, res) => {
|
|
const pending = await approvalQueue.getPending();
|
|
|
|
res.render('approvals', {
|
|
items: pending.map(item => ({
|
|
type: item.type,
|
|
description: item.description,
|
|
ai_reasoning: item.ai_reasoning,
|
|
concerns: item.concerns,
|
|
approve_url: `/admin/approve/${item.id}`,
|
|
reject_url: `/admin/reject/${item.id}`
|
|
}))
|
|
});
|
|
});
|
|
```
|
|
|
|
---
|
|
|
|
## Testing
|
|
|
|
### Unit Tests
|
|
|
|
```javascript
|
|
const { InstructionPersistenceClassifier } = require('tractatus-framework');
|
|
|
|
describe('InstructionPersistenceClassifier', () => {
|
|
test('classifies SYSTEM instruction correctly', () => {
|
|
const classifier = new InstructionPersistenceClassifier();
|
|
const result = classifier.classify({
|
|
text: 'Use MongoDB on port 27017',
|
|
source: 'user'
|
|
});
|
|
|
|
expect(result.quadrant).toBe('SYSTEM');
|
|
expect(result.persistence).toBe('HIGH');
|
|
expect(result.explicitness).toBeGreaterThan(0.8);
|
|
});
|
|
});
|
|
```
|
|
|
|
### Integration Tests
|
|
|
|
```javascript
|
|
describe('Tractatus Integration', () => {
|
|
test('prevents 27027 incident', async () => {
|
|
// Store user's explicit instruction (non-standard port)
|
|
await instructionDB.store({
|
|
text: 'Check MongoDB at port 27027',
|
|
quadrant: 'SYSTEM',
|
|
persistence: 'HIGH',
|
|
parameters: { port: '27027' },
|
|
note: 'Conflicts with training pattern (27017)'
|
|
});
|
|
|
|
// AI tries to use training pattern default (27017) instead
|
|
const validation = await validator.validate(
|
|
{ type: 'db_connect', parameters: { port: 27017 } },
|
|
{ explicit_instructions: await instructionDB.getActive() }
|
|
);
|
|
|
|
expect(validation.status).toBe('REJECTED');
|
|
expect(validation.reason).toContain('pattern recognition bias');
|
|
expect(validation.conflict_type).toBe('training_pattern_override');
|
|
});
|
|
});
|
|
```
|
|
|
|
---
|
|
|
|
## Troubleshooting
|
|
|
|
### Issue: Instructions not persisting
|
|
|
|
**Cause**: Explicitness score too low
|
|
**Solution**: Lower `min_explicitness` threshold or rephrase instruction more explicitly
|
|
|
|
### Issue: Too many false positives in validation
|
|
|
|
**Cause**: Conflict detection too strict
|
|
**Solution**: Increase `conflict_tolerance` or refine parameter extraction
|
|
|
|
### Issue: Pressure monitoring too sensitive
|
|
|
|
**Cause**: Thresholds too low for your use case
|
|
**Solution**: Adjust pressure thresholds based on observed quality degradation
|
|
|
|
### Issue: Boundary enforcer blocking too much
|
|
|
|
**Cause**: Domain classification too broad
|
|
**Solution**: Refine domain definitions or add exceptions
|
|
|
|
---
|
|
|
|
## Production Deployment
|
|
|
|
### Checklist
|
|
|
|
- [ ] Instruction database backed up regularly
|
|
- [ ] Audit logs enabled for all governance decisions
|
|
- [ ] Pressure monitoring configured with appropriate thresholds
|
|
- [ ] Human oversight queue monitored 24/7
|
|
- [ ] Fallback to human review if services fail
|
|
- [ ] Performance monitoring (service overhead < 50ms per check)
|
|
- [ ] Security review of instruction storage
|
|
- [ ] GDPR compliance for instruction data
|
|
|
|
### Performance Considerations
|
|
|
|
```javascript
|
|
// Cache active instructions
|
|
const cache = new Map();
|
|
setInterval(() => {
|
|
instructionDB.getActive().then(instructions => {
|
|
cache.set('active', instructions);
|
|
});
|
|
}, 60000); // Refresh every minute
|
|
|
|
// Use cached instructions
|
|
const validation = validator.validate(
|
|
action,
|
|
{ explicit_instructions: cache.get('active') }
|
|
);
|
|
```
|
|
|
|
---
|
|
|
|
## Next Steps
|
|
|
|
- **[Case Studies](https://agenticgovernance.digital/docs.html?category=case-studies)** - Real-world examples
|
|
- **[Core Concepts](https://agenticgovernance.digital/docs.html?doc=core-concepts-of-the-tractatus-framework)** - Deep dive into services
|
|
- **[Interactive Demo](/demos/27027-demo.html)** - Try the framework yourself
|
|
- **[GitHub Repository](https://github.com/anthropics/tractatus)** - Source code and contributions
|
|
|
|
---
|
|
|
|
## Document Metadata
|
|
|
|
<div class="document-metadata">
|
|
|
|
- **Version:** 1.0
|
|
- **Created:** 2025-10-12
|
|
- **Last Modified:** 2025-10-13
|
|
- **Author:** SyDigital Ltd
|
|
- **Word Count:** 2,248 words
|
|
- **Reading Time:** ~12 minutes
|
|
- **Document ID:** implementation-guide
|
|
- **Status:** Active
|
|
|
|
</div>
|
|
|
|
---
|
|
|
|
## License
|
|
|
|
Copyright 2025 John Stroh
|
|
|
|
Licensed under the European Union Public Licence, Version 1.2 (the "Licence"); you may not use this file except in compliance with the Licence. You may obtain a copy of the Licence at:
|
|
|
|
https://interoperable-europe.ec.europa.eu/collection/eupl/eupl-text-eupl-12
|
|
|
|
Unless required by applicable law or agreed to in writing, software distributed under the Licence is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the Licence for the specific language governing permissions and limitations under the Licence.
|
|
|
|
**Full Licence Text:**
|
|
|
|
For the full EUPL-1.2 licence text, see:
|
|
https://interoperable-europe.ec.europa.eu/collection/eupl/eupl-text-eupl-12
|
|
|
|
The EUPL-1.2 is available in 23 official EU-language versions at the same source.
|
|
|
|
---
|
|
|
|
**Questions?** Contact: john.stroh.nz@pm.me
|