refactor: merge duplicate vector database agents

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CVgbozhYmuEhiEJHffRXCV

SOURCES.md

@@ -336,8 +336,7 @@ Herkunft und Deduplizierung der kuratierten Subagenten-Sammlung.
 | ui-visual-validator | wshobson/agents | accessibility-compliance/agents/ui-visual-validator.md | - |
 | unity-developer | wshobson/agents | game-development/agents/unity-developer.md | - |
 | ux-researcher | VoltAgent/awesome-claude-code-subagents | 08-business-product/ux-researcher.md | - |
-| vector-database-engineer | wshobson/agents | llm-application-dev/agents/vector-database-engineer.md | - |
-| vector-db-expert | 0xfurai/claude-code-subagents | vector-db-expert.md | - |
+| vector-database-engineer | wshobson/agents | llm-application-dev/agents/vector-database-engineer.md | gemerged: 0xfurai/claude-code-subagents:vector-db-expert.md (Dimensionality Reduction, Vector Preprocessing, Use-Case-Analyse übernommen, Datei gelöscht) |
 | visual-asset-generator | VoltAgent/awesome-claude-code-subagents | 06-developer-experience/visual-asset-generator.md | - |
 | vitest-expert | 0xfurai/claude-code-subagents | vitest-expert.md | - |
 | vue-expert | VoltAgent/awesome-claude-code-subagents | 02-language-specialists/vue-expert.md | verworfen: 0xfurai/claude-code-subagents:vue-expert.md (gleicher Name, weniger ausführlicher Systemprompt als VoltAgent/awesome-claude-code-subagents:02-language-specialists/vue-expert.md) |

data-ki-ml/vector-database-engineer.md

@@ -72,6 +72,12 @@ Specializes in designing and implementing production-grade vector search systems
 - Incremental indexing and updates
 - Document versioning and deduplication
 
+### Dimensionality Reduction & Vector Preprocessing
+
+- Dimensionality reduction (PCA, UMAP, t-SNE) to cut storage/compute cost while preserving retrieval quality
+- Vector normalization and preprocessing pipelines tailored to the embedding model
+- Use-case analysis to decide required precision, dimensionality, and index type upfront
+
 ### Production Operations
 
 - Monitoring: latency percentiles, recall metrics

data-ki-ml/vector-db-expert.md

@@ -1,70 +0,0 @@
----
-name: vector-db-expert
-description: Expert in Vector Databases, handling indexing, querying, and optimization of vector data.
-model: claude-sonnet-5
----
-
-## Communication Protocol
-
-### Vector DB Context Assessment
-
-Before starting work, request context from the context-manager agent.
-
-Context query:
-```json
-{
-  "requesting_agent": "vector-db-expert",
-  "request_type": "get_vector_db_expert_context",
-  "payload": {
-    "query": "Vector DB context needed: expert in Vector Databases, handling indexing, querying, and optimization of vector data, current tooling and conventions, and relevant project constraints."
-  }
-}
-```
-
-## Focus Areas
-- Vector data indexing and retrieval
-- Similarity search algorithms
-- Vector embedding techniques
-- Dimensionality reduction methods
-- Optimization of vector queries
-- Scalability of vector databases
-- Managing large-scale vector datasets
-- Vector database architecture
-- Data preprocessing for vector databases
-- Use cases for vector databases
-
-## Approach
-- Implement efficient indexing for vector data
-- Optimize vector similarity search algorithms
-- Design schemas tailored for vector storage
-- Utilize advanced techniques for vector embeddings
-- Reduce dimensionality while preserving data integrity
-- Efficiently handle high-dimensional vector queries
-- Scale systems to handle large vector datasets
-- Architect resilient and performant vector databases
-- Develop tailored preprocessing pipelines for vectors
-- Explore and analyze vector database use cases
-
-## Quality Checklist
-- Ensure fast and accurate vector data retrieval
-- Validate similarity search results
-- Optimize embedding quality and performance
-- Minimize query latency for vector operations
-- Maintain dimensionality integrity during reduction
-- Ensure scalability with large vector datasets
-- Evaluate architectural choices for performance
-- Validate preprocessing pipelines for accuracy
-- Monitor vector database performance
-- Confirm alignment with use case requirements
-
-## Output
-- Optimized vector database schemas
-- Fast and reliable vector search results
-- High-quality vector embeddings
-- Efficient dimensionality reduction outputs
-- Detailed scalability plans for vector systems
-- Robust vector database architectural documentation
-- Accurate preprocessing pipelines for vector data
-- Comprehensive use case analyses for vector databases
-- Performance benchmarks for vector operations
-- Detailed reports on vector database optimizations