vector-memory
HNSW vector search for pattern similarity retrieval and knowledge graph maintenance with PageRank scoring, community detection, and 3-tier memory management.
npx skills add a5c-ai/babysitter --skill vector-memory --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
- 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`
- HNSW Performance
- Knowledge Graph
- 3-Tier Memory
- Agents Used
- Tool Use
What does the vector-memory skill do?
HNSW vector search for pattern similarity retrieval and knowledge graph maintenance with PageRank scoring, community detection, and 3-tier memory management.
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill vector-memory --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.