memory-search
SOTA semantic search — hybrid (sparse+dense), Graph RAG multi-hop, MMR diversity reranking, recency weighting
How do I install this agent skill?
npx skills add https://github.com/ruvnet/ruflo --skill memory-searchIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The skill provides state-of-the-art memory search and semantic retrieval procedures using local or standard tools. No security issues were identified.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
What does this agent skill do?
Memory Search (SOTA)
State-of-the-art semantic search across Ruflo memory with multiple retrieval strategies.
Strategy Selection
Choose based on query type:
- Default (dense): fast single-hop semantic match
- --hybrid: sparse + dense with RRF fusion (20-49% better for keyword+semantic queries)
- --graph-rag: multi-hop knowledge retrieval (30-60% better for reasoning queries)
Steps
-
Parse query and flags — extract search text and strategy flags from arguments
-
Select retrieval strategy:
Dense search (default):
npx @claude-flow/cli@latest memory search --query "QUERY" --namespace NAMESPACE --limit 10Or via MCP:
mcp__plugin_ruflo-core_ruflo__memory_search({ query: "QUERY", namespace: "NAMESPACE", limit: 10 })Hybrid search (when --hybrid or query has specific keywords):
npx ruvector search "QUERY" --hybrid --limit 10Graph RAG (when --graph-rag or multi-hop reasoning needed):
npx ruvector search "QUERY" --graph-rag --limit 10Smart retrieval (when --smart or complex recall needed):
npx @claude-flow/cli@latest memory search --query "QUERY" --smart --limit 10Or via MCP:
mcp__plugin_ruflo-core_ruflo__memory_search({ query: "QUERY", smart: true, limit: 10 })Applies 5-phase pipeline: query expansion, RRF fusion, recency boost, MMR diversity, session round-robin. Best for: multi-session recall, temporal queries, diverse result sets.
Unified cross-namespace:
mcp__plugin_ruflo-core_ruflo__memory_search_unified({ query: "QUERY", limit: 10 }) -
Apply MMR reranking — for diverse results, filter near-duplicates (cosine > 0.92) while maximizing relevance
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Apply recency weighting — boost recent entries with exponential decay (0.95/day)
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Synthesize context (for complex queries):
mcp__plugin_ruflo-core_ruflo__agentdb_context-synthesize({ query: "QUERY", sources: ["patterns", "tasks", "solutions"] }) -
Present results — ranked by composite score (relevance * diversity * recency), with source namespace attribution
Namespace Guide
| Namespace | Best For |
|---|---|
patterns | "How did we handle X?" |
tasks | "What was the context for Y?" |
solutions | "How did we fix Z?" |
feedback | "What did the user prefer?" |
security | "Known vulnerabilities in..." |
| (omit) | Search all namespaces |
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/ruvnet/ruflo/memory-search">View memory-search on skillZs</a>