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Get Started Free →SOTA semantic search — hybrid (sparse+dense), Graph RAG multi-hop, MMR diversity reranking, recency weighting
.claude/skills/ruvnet-memory-search/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-16 | ✗→✓ | ▲ Improved | -47% | 0% |
| case-17 | ✗→✓ | ▲ Improved | -44% | 0% |
| case-19 | ✗→✓ | ▲ Improved | 24% | 0% |
| case-20 | ✗→✓ | ▲ Improved | -18% | 0% |
| case-21 | ✗→✓ | ▲ Improved | -14% | 0% |
State-of-the-art semantic search across Ruflo memory with multiple retrieval strategies.
Choose based on query type:
Dense search (default): bash 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): bash npx ruvector search "QUERY" --hybrid --limit 10
Graph RAG (when --graph-rag or multi-hop reasoning needed): bash npx ruvector search "QUERY" --graph-rag --limit 10
Smart retrieval (when --smart or complex recall needed): bash 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 })
mcp__plugin_ruflo-core_ruflo__agentdb_context-synthesize({ query: "QUERY", sources: ["patterns", "tasks", "solutions"] })
| 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 |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 4,025 | 10,914 | +171% | 1 | 1 | 0% | 704 | 1,852 | +163% | 0 | 0 | — |
case-02 | fail→fail | 12,046 | 7,847 | -35% | 1 | 1 | 0% | 1,999 | 1,289 | -36% | 0 | 0 | — |
case-03 | pass→fail | 14,804 | 9,275 | -37% | 1 | 1 | 0% | 2,748 | 1,212 | -56% | 0 | 0 | — |
case-04 | fail→fail | 10,426 | 16,133 | +55% | 1 | 1 | 0% | 1,416 | 1,619 | +14% | 0 | 0 | — |
case-05 | pass→pass | 6,048 | 10,063 | +66% | 1 | 1 | 0% | 1,171 | 2,485 | +112% | 0 | 0 | — |
case-06 | pass→pass | 9,690 | 9,596 | -1% | 1 | 1 | 0% | 1,901 | 2,453 | +29% | 0 | 0 | — |
case-07 | fail→fail | 11,926 | 9,468 | -21% | 1 | 1 | 0% | 2,234 | 1,287 | -42% | 0 | 0 | — |
case-08 | fail→fail | 15,137 | 16,752 | +11% | 1 | 1 | 0% | 2,367 | 3,022 | +28% | 0 | 0 | — |
case-09 | fail→fail | 19,779 | 11,102 | -44% | 1 | 1 | 0% | 3,299 | 1,246 | -62% | 0 | 0 | — |
case-10 | fail→fail | 14,811 | 5,428 | -63% | 1 | 1 | 0% | 2,836 | 1,090 | -62% | 0 | 0 | — |
case-11 | fail→fail | 6,555 | 5,591 | -15% | 1 | 1 | 0% | 1,079 | 998 | -8% | 0 | 0 | — |
case-12 | fail→fail | 11,049 | 7,331 | -34% | 1 | 1 | 0% | 1,859 | 1,396 | -25% | 0 | 0 | — |
case-13 | fail→fail | 8,386 | 7,321 | -13% | 1 | 1 | 0% | 1,376 | 1,018 | -26% | 0 | 0 | — |
case-14 | fail→fail | 10,985 | 5,867 | -47% | 1 | 1 | 0% | 2,089 | 1,136 | -46% | 0 | 0 | — |
case-15 | fail→fail | 3,380 | 6,612 | +96% | 1 | 1 | 0% | 425 | 1,339 | +215% | 0 | 0 | — |
case-16 | fail→pass | 14,166 | 2,812 | -80% | 1 | 1 | 0% | 2,302 | 1,222 | -47% | 0 | 0 | — |
case-17 | fail→pass | 11,367 | 3,534 | -69% | 1 | 1 | 0% | 2,409 | 1,359 | -44% | 0 | 0 | — |
case-18 | fail→fail | 20,588 | 19,791 | -4% | 1 | 1 | 0% | 3,621 | 3,447 | -5% | 0 | 0 | — |
case-19 | fail→pass | 8,099 | 5,796 | -28% | 1 | 1 | 0% | 1,334 | 1,658 | +24% | 0 | 0 | — |
case-20 | fail→pass | 15,287 | 6,731 | -56% | 1 | 1 | 0% | 2,456 | 2,020 | -18% | 0 | 0 | — |
case-21 | fail→pass | 13,929 | 7,173 | -49% | 1 | 1 | 0% | 2,487 | 2,145 | -14% | 0 | 0 | — |
case-22 | fail→fail | 8,075 | 5,057 | -37% | 1 | 1 | 0% | 1,432 | 999 | -30% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 9 counted toward the lift figure. The other 13 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +18 percentage points is the difference between those two pass rates over the 9 comparable cases. 3 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.