vector-memory
HNSW vector search for pattern similarity retrieval and knowledge graph maintenance with PageRank scoring, community detection, and 3-tier memory management.
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- Dépôt
- a5c-ai/babysitter
- Dernière activité de la source
- 1 juin 2026 à 07:46
- Langue détectée de SKILL.md
- anglais
- Étoiles
- 1 832
- Forks
- 113
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SKILL.md
Instructions source · Aperçu en lecture seule- name
- vector-memory
- description
- HNSW vector search for pattern similarity retrieval and knowledge graph maintenance with PageRank scoring, community detection, and 3-tier memory management.
- allowed-tools
- Read, Write, Edit, Bash, Grep, Glob, WebFetch, WebSearch, Agent, AskUserQuestion
- graph
- {"domains":["domain:software-engineering"],"skillAreas":["skill-area:agentic-loops","skill-area:orchestration-loop"],"workflows":["workflow:feature-development"],"topics":["topic:developer-experience"],"roles":["role:tech-lead","role:backend-engineer"]}
- Building and querying knowledge graphs for project context
- Managing cross-session memory across project/local/user scopes
- Fast similarity search for routing decisions
## HNSW Performance
- Search latency: ~61 microseconds
- Query throughput: ~16,400 QPS
- Configurable embedding dimensions (default: 128)
## Knowledge Graph
- **PageRank**: Importance scoring for knowledge nodes
- **Community Detection**: Cluster related patterns
- **LRU Cache**: Fast access to frequently used patterns
- **SQLite Backing**: Persistent cross-session storage
## 3-Tier Memory
| Scope | Persistence | Content |
|-------|------------|---------|
| Project | Codebase-level | Patterns, architecture decisions, dependencies |
| Local | Session-level | Context, adaptations, temporary patterns |
| User | Cross-project | Preferences, learned behaviors, global patterns |
## Agents Used
- `agents/optimizer/` - Memory and cache optimization
## Tool Use
Invoke via babysitter process: `methodologies/ruflo/ruflo-intelligence`
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