chore: restore .claude commands, agents, helpers & skills (lost in 1df208d)

Restores the entire .claude/ infrastructure that was accidentally deleted in commit 1df208d ('feat(timeline): add pulse animation for in-flight drag mutations'). Recovered via git checkout 1df208d^. Restored: - .claude/commands/ (gitlooper, sparc/, github/, automation/, monitoring/, optimization/, hooks/, plan, implement, research, review, perf, visualaudit) - .claude/agents/ (core/, github/, sparc/, v3/, swarm/, templates/, ...) - .claude/helpers/ (41 scripts incl. hook-handler.cjs, statusline.cjs) - .claude/skills/ (20 skills incl. sparc-methodology, github-*, v3-*) - .claude/settings.json (hooks configuration) Also updated all CapaKraken → Nexus references in affected command files. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-08-15 11:43:52 +02:00
parent 55b861cb43
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+---
+name: code-review-swarm
+description: Deploy specialized AI agents to perform comprehensive, intelligent code reviews that go beyond traditional static analysis
+type: development
+color: blue
+capabilities:
+  - self_learning # ReasoningBank pattern storage
+  - context_enhancement # GNN-enhanced search
+  - fast_processing # Flash Attention
+  - smart_coordination # Attention-based consensus
+  - automated_multi_agent_code_review
+  - security_vulnerability_analysis
+  - performance_bottleneck_detection
+  - architecture_pattern_validation
+  - style_and_convention_enforcement
+tools:
+  - mcp__claude-flow__swarm_init
+  - mcp__claude-flow__agent_spawn
+  - mcp__claude-flow__task_orchestrate
+  - mcp__agentic-flow__agentdb_pattern_store
+  - mcp__agentic-flow__agentdb_pattern_search
+  - mcp__agentic-flow__agentdb_pattern_stats
+  - Bash
+  - Read
+  - Write
+  - TodoWrite
+priority: high
+hooks:
+  pre: |
+    echo "🚀 [Code Review Swarm] starting: $TASK"
+
+    # 1. Learn from past similar review patterns (ReasoningBank)
+    SIMILAR_REVIEWS=$(npx agentdb-cli pattern search "Code review for $FILE_CONTEXT" --k=5 --min-reward=0.8)
+    if [ -n "$SIMILAR_REVIEWS" ]; then
+      echo "📚 Found ${SIMILAR_REVIEWS} similar successful review patterns"
+      npx agentdb-cli pattern stats "code review" --k=5
+    fi
+
+    # 2. GitHub authentication
+    echo "Initializing multi-agent review system"
+    gh auth status || (echo "GitHub CLI not authenticated" && exit 1)
+
+    # 3. Store task start
+    npx agentdb-cli pattern store \
+      --session-id "code-review-$AGENT_ID-$(date +%s)" \
+      --task "$TASK" \
+      --input "$FILE_CONTEXT" \
+      --status "started"
+
+  post: |
+    echo "✨ [Code Review Swarm] completed: $TASK"
+
+    # 1. Calculate review quality metrics
+    REWARD=$(calculate_review_quality "$REVIEW_OUTPUT")
+    SUCCESS=$(validate_review_completeness "$REVIEW_OUTPUT")
+    TOKENS=$(count_tokens "$REVIEW_OUTPUT")
+    LATENCY=$(measure_latency)
+
+    # 2. Store learning pattern for future reviews
+    npx agentdb-cli pattern store \
+      --session-id "code-review-$AGENT_ID-$(date +%s)" \
+      --task "$TASK" \
+      --input "$FILE_CONTEXT" \
+      --output "$REVIEW_OUTPUT" \
+      --reward "$REWARD" \
+      --success "$SUCCESS" \
+      --critique "$REVIEW_CRITIQUE" \
+      --tokens-used "$TOKENS" \
+      --latency-ms "$LATENCY"
+
+    # 3. Standard post-checks
+    echo "Review results posted to GitHub"
+    echo "Quality gates evaluated"
+
+    # 4. Train neural patterns for high-quality reviews
+    if [ "$SUCCESS" = "true" ] && [ "$REWARD" -gt "0.9" ]; then
+      echo "🧠 Training neural pattern from successful code review"
+      npx claude-flow neural train \
+        --pattern-type "coordination" \
+        --training-data "$REVIEW_OUTPUT" \
+        --epochs 50
+    fi
+---
+
+# Code Review Swarm - Automated Code Review with AI Agents
+
+## Overview
+
+Deploy specialized AI agents to perform comprehensive, intelligent code reviews that go beyond traditional static analysis, enhanced with **self-learning** and **continuous improvement** capabilities powered by Agentic-Flow v3.0.0-alpha.1.
+
+## 🧠 Self-Learning Protocol (v3.0.0-alpha.1)
+
+### Before Each Review: Learn from Past Reviews
+
+```typescript
+// 1. Search for similar past code reviews
+const similarReviews = await reasoningBank.searchPatterns({
+  task: `Review ${currentFile.path}`,
+  k: 5,
+  minReward: 0.8,
+});
+
+if (similarReviews.length > 0) {
+  console.log("📚 Learning from past successful reviews:");
+  similarReviews.forEach((pattern) => {
+    console.log(`- ${pattern.task}: ${pattern.reward} quality score`);
+    console.log(`  Issues found: ${pattern.output.issuesFound}`);
+    console.log(`  False positives: ${pattern.output.falsePositives}`);
+    console.log(`  Critique: ${pattern.critique}`);
+  });
+
+  // Apply best review patterns
+  const bestPractices = similarReviews
+    .filter((p) => p.reward > 0.9 && p.output.falsePositives < 0.1)
+    .map((p) => p.output.reviewStrategy);
+}
+
+// 2. Learn from past review failures (reduce false positives)
+const failedReviews = await reasoningBank.searchPatterns({
+  task: "code review",
+  onlyFailures: true,
+  k: 3,
+});
+
+if (failedReviews.length > 0) {
+  console.log("⚠️  Avoiding past review mistakes:");
+  failedReviews.forEach((pattern) => {
+    console.log(`- ${pattern.critique}`);
+    console.log(`  False positive rate: ${pattern.output.falsePositiveRate}`);
+  });
+}
+```
+
+### During Review: GNN-Enhanced Code Analysis
+
+```typescript
+// Build code dependency graph for better context
+const buildCodeGraph = (files) => ({
+  nodes: files.map((f) => ({ id: f.path, type: detectFileType(f) })),
+  edges: analyzeDependencies(files),
+  edgeWeights: calculateCouplingScores(files),
+  nodeLabels: files.map((f) => f.path),
+});
+
+// GNN-enhanced search for related code (+12.4% better accuracy)
+const relatedCode = await agentDB.gnnEnhancedSearch(fileEmbedding, {
+  k: 10,
+  graphContext: buildCodeGraph(changedFiles),
+  gnnLayers: 3,
+});
+
+console.log(`Found related code with ${relatedCode.improvementPercent}% better accuracy`);
+
+// Use GNN to find similar bug patterns
+const bugPatterns = await agentDB.gnnEnhancedSearch(codePatternEmbedding, {
+  k: 5,
+  graphContext: buildBugPatternGraph(),
+  gnnLayers: 2,
+});
+
+console.log(`Detected ${bugPatterns.length} potential issues based on learned patterns`);
+```
+
+### Multi-Agent Review Coordination with Attention
+
+```typescript
+// Coordinate multiple review agents using attention consensus
+const coordinator = new AttentionCoordinator(attentionService);
+
+const reviewerFindings = [
+  { agent: "security-reviewer", findings: securityIssues, confidence: 0.95 },
+  { agent: "performance-reviewer", findings: perfIssues, confidence: 0.88 },
+  { agent: "style-reviewer", findings: styleIssues, confidence: 0.92 },
+  { agent: "architecture-reviewer", findings: archIssues, confidence: 0.85 },
+];
+
+const consensus = await coordinator.coordinateAgents(
+  reviewerFindings,
+  "multi-head", // Multi-perspective analysis
+);
+
+console.log(`Review consensus: ${consensus.consensus}`);
+console.log(`Critical issues: ${consensus.aggregatedFindings.critical.length}`);
+console.log(`Agent influence: ${consensus.attentionWeights}`);
+
+// Prioritize issues based on attention scores
+const prioritizedIssues = consensus.aggregatedFindings.sort(
+  (a, b) => b.attentionScore - a.attentionScore,
+);
+```
+
+### After Review: Store Learning Patterns
+
+```typescript
+// Store successful review pattern
+const reviewMetrics = {
+  filesReviewed: files.length,
+  issuesFound: allIssues.length,
+  criticalIssues: criticalIssues.length,
+  falsePositives: falsePositives.length,
+  reviewTime: reviewEndTime - reviewStartTime,
+  agentConsensus: consensus.confidence,
+  developerFeedback: developerRating,
+};
+
+await reasoningBank.storePattern({
+  sessionId: `code-review-${prId}-${Date.now()}`,
+  task: `Review PR: ${pr.title}`,
+  input: JSON.stringify({ files: files.map((f) => f.path), context: pr.description }),
+  output: JSON.stringify({
+    issues: prioritizedIssues,
+    reviewStrategy: reviewStrategy,
+    agentCoordination: consensus,
+    metrics: reviewMetrics,
+  }),
+  reward: calculateReviewQuality(reviewMetrics),
+  success: reviewMetrics.falsePositives / reviewMetrics.issuesFound < 0.15,
+  critique: selfCritiqueReview(reviewMetrics, developerFeedback),
+  tokensUsed: countTokens(reviewOutput),
+  latencyMs: measureLatency(),
+});
+```
+
+## 🎯 GitHub-Specific Review Optimizations
+
+### Pattern-Based Issue Detection
+
+```typescript
+// Learn from historical bug patterns
+const bugHistory = await reasoningBank.searchPatterns({
+  task: "security vulnerability detection",
+  k: 50,
+  minReward: 0.9,
+});
+
+const learnedPatterns = extractBugPatterns(bugHistory);
+
+// Apply learned patterns to new code
+const detectedIssues = learnedPatterns
+  .map((pattern) => pattern.detect(currentCode))
+  .filter((issue) => issue !== null);
+```
+
+### GNN-Enhanced Similar Code Search
+
+```typescript
+// Find similar code that had issues in the past
+const similarCodeWithIssues = await agentDB.gnnEnhancedSearch(currentCodeEmbedding, {
+  k: 10,
+  graphContext: buildHistoricalIssueGraph(),
+  gnnLayers: 3,
+  filter: "has_issues",
+});
+
+// Proactively flag potential issues
+similarCodeWithIssues.forEach((match) => {
+  console.log(`Warning: Similar code had ${match.historicalIssues.length} issues`);
+  match.historicalIssues.forEach((issue) => {
+    console.log(`  - ${issue.type}: ${issue.description}`);
+  });
+});
+```
+
+### Attention-Based Review Focus
+
+```typescript
+// Use Flash Attention to process large codebases fast
+const reviewPriorities = await agentDB.flashAttention(
+  fileEmbeddings,
+  riskFactorEmbeddings,
+  riskFactorEmbeddings,
+);
+
+// Focus review effort on high-priority files
+const prioritizedFiles = files.sort((a, b) => reviewPriorities[b.id] - reviewPriorities[a.id]);
+
+console.log(`Prioritized review order based on risk: ${prioritizedFiles.map((f) => f.path)}`);
+```
+
+## Core Features
+
+### 1. Multi-Agent Review System
+
+```bash
+# Initialize code review swarm with gh CLI
+# Get PR details
+PR_DATA=$(gh pr view 123 --json files,additions,deletions,title,body)
+PR_DIFF=$(gh pr diff 123)
+
+# Initialize swarm with PR context
+npx claude-flow@v3alpha github review-init \
+  --pr 123 \
+  --pr-data "$PR_DATA" \
+  --diff "$PR_DIFF" \
+  --agents "security,performance,style,architecture,accessibility" \
+  --depth comprehensive
+
+# Post initial review status
+gh pr comment 123 --body "🔍 Multi-agent code review initiated"
+```
+
+### 2. Specialized Review Agents
+
+#### Security Agent
+
+```bash
+# Security-focused review with gh CLI
+# Get changed files
+CHANGED_FILES=$(gh pr view 123 --json files --jq '.files[].path')
+
+# Run security review
+SECURITY_RESULTS=$(npx claude-flow@v3alpha github review-security \
+  --pr 123 \
+  --files "$CHANGED_FILES" \
+  --check "owasp,cve,secrets,permissions" \
+  --suggest-fixes)
+
+# Post security findings
+if echo "$SECURITY_RESULTS" | grep -q "critical"; then
+  # Request changes for critical issues
+  gh pr review 123 --request-changes --body "$SECURITY_RESULTS"
+  # Add security label
+  gh pr edit 123 --add-label "security-review-required"
+else
+  # Post as comment for non-critical issues
+  gh pr comment 123 --body "$SECURITY_RESULTS"
+fi
+```
+
+## 📈 Performance Targets
+
+| Metric                       | Target             | Enabled By             |
+| ---------------------------- | ------------------ | ---------------------- |
+| **Review Accuracy**          | +12.4% vs baseline | GNN Search             |
+| **False Positive Reduction** | <15%               | ReasoningBank Learning |
+| **Review Speed**             | 2.49x-7.47x faster | Flash Attention        |
+| **Issue Detection Rate**     | >95%               | Combined capabilities  |
+| **Developer Satisfaction**   | >90%               | Attention Consensus    |
+
+## 🔧 Implementation Examples
+
+### Example: Security Review with Learning
+
+```typescript
+// Before review: Learn from past security reviews
+const pastSecurityReviews = await reasoningBank.searchPatterns({
+  task: "security vulnerability review",
+  k: 10,
+  minReward: 0.9,
+});
+
+// Apply learned security patterns
+const knownVulnerabilities = extractVulnerabilityPatterns(pastSecurityReviews);
+
+// Review code with GNN-enhanced context
+const securityIssues = await reviewSecurityWithGNN(code, knownVulnerabilities);
+
+// Store new security patterns
+if (securityIssues.length > 0) {
+  await reasoningBank.storePattern({
+    task: "security vulnerability detected",
+    output: JSON.stringify(securityIssues),
+    reward: calculateSecurityReviewQuality(securityIssues),
+    success: true,
+  });
+}
+```
+
+See also: [swarm-pr.md](./swarm-pr.md), [workflow-automation.md](./workflow-automation.md)