/memory-search
SOTA semantic search — hybrid (sparse+dense), Graph RAG multi-hop, MMR diversity reranking, recency weighting
$ npx -y skills add ruvnet/ruflo --skill memory-search --agent claude-codeHow it fires
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/memory-search
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SOTA semantic search — hybrid (sparse+dense), Graph RAG multi-hop, MMR diversity reranking, recency weighting
SKILL.md
memory-search.SKILL.mdname: memory-search
description: SOTA semantic search — hybrid (sparse+dense), Graph RAG multi-hop, MMR diversity reranking, recency weighting
allowed-tools: Bash Read mcp__plugin_ruflo-core_ruflo__memory_search mcp__plugin_ruflo-core_ruflo__memory_store mcp__plugin_ruflo-core_ruflo__memory_list mcp__plugin_ruflo-core_ruflo__memory_retrieve mcp__plugin_ruflo-core_ruflo__memory_search_unified mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search mcp__plugin_ruflo-core_ruflo__agentdb_context-synthesize
argument-hint: "<query> [--hybrid] [--graph-rag] [--namespace NAME]"
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
1. **Parse query and flags** — extract search text and strategy flags from arguments 2. **Select retrieval strategy**:
**Dense search (default)**:
npx @claude-flow/cli@latest memory search --query "QUERY" --namespace NAMESPACE --limit 10
Or 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 10
**Graph RAG** (when --graph-rag or multi-hop reasoning needed):
npx ruvector search "QUERY" --graph-rag --limit 10
**Smart retrieval** (when --smart or complex recall needed):
npx @claude-flow/cli@latest memory search --query "QUERY" --smart --limit 10
Or 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 })`
3. **Apply MMR reranking** — for diverse results, filter near-duplicates (cosine > 0.92) while maximizing relevance 4. **Apply recency weighting** — boost recent entries with exponential decay (0.95/day) 5. **Synthesize context** (for complex queries): `mcp__plugin_ruflo-core_ruflo__agentdb_context-synthesize({ query: "QUERY", sources: ["patterns", "tasks", "solutions"] })` 6. **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 |
Read more
name: memory-search description: SOTA semantic search — hybrid (sparse+dense), Graph RAG multi-hop, MMR diversity reranking, recency weighting allowed-tools: Bash Read mcp__plugin_ruflo-core_ruflo__memory_search mcp__plugin_ruflo-core_ruflo__memory_store mcp__plugin_ruflo-core_ruflo__memory_list mcp__plugin_ruflo-core_ruflo__memory_retrieve mcp__plugin_ruflo-core_ruflo__memory_search_unified mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search mcp__plugin_ruflo-core_ruflo__agentdb_context-synthesize argument-hint: "<query> [--hybrid] [--graph-rag] [--namespace NAME]"
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
1. **Parse query and flags** — extract search text and strategy flags from arguments 2. **Select retrieval strategy**:
**Dense search (default)**:
npx @claude-flow/cli@latest memory search --query "QUERY" --namespace NAMESPACE --limit 10
Or 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 10
**Graph RAG** (when --graph-rag or multi-hop reasoning needed):
npx ruvector search "QUERY" --graph-rag --limit 10
**Smart retrieval** (when --smart or complex recall needed):
npx @claude-flow/cli@latest memory search --query "QUERY" --smart --limit 10
Or 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 })`
3. **Apply MMR reranking** — for diverse results, filter near-duplicates (cosine > 0.92) while maximizing relevance 4. **Apply recency weighting** — boost recent entries with exponential decay (0.95/day) 5. **Synthesize context** (for complex queries): `mcp__plugin_ruflo-core_ruflo__agentdb_context-synthesize({ query: "QUERY", sources: ["patterns", "tasks", "solutions"] })` 6. **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 |
An agent meta-harness for Claude Code and Codex. Agent = Model + Harness. The model writes; the harness gives it tools, memory, loops, sandboxes, and controls so it can actually work.
Repo: ruvnet/ruflo
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