Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Publish or fetch learned patterns across projects via IPFS (Pinata) -- the cross-project pattern transfer that hooks_transfer enables
.claude/skills/ruvnet-intelligence-transfer/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | -29% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -33% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 28% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 21% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -20% | 0% |
Cross-project pattern sharing via IPFS. Lets a different project — or a different machine — fetch and apply patterns this project has already learned.
Most learning is project-local. hooks_transfer is the escape hatch: publish patterns to IPFS, share the CID, and any peer can ingest them. Equivalent to "a deploy artifact for what your agents have learned."
bash# Required env var (or equivalent endpoint config) echo $PINATA_API_JWT
If unset, hooks_transfer returns a structured success: false with error: "PINATA_API_JWT not configured". Configure before running this skill.
bash# Inspect what's stored locally first mcp tool call neural_patterns --json -- '{"list": true}' # Publish to IPFS — returns a CID mcp tool call hooks_transfer --json -- '{"action": "store"}'
The response includes the IPFS CID. Save it; share it with peers who need the patterns.
bash# Pull a CID and apply locally mcp tool call hooks_transfer --json -- '{"action": "load", "cid": "QmXyz..."}' # Verify they landed mcp tool call hooks_intelligence_pattern-search --json -- '{"query": "<test>", "limit": 5}'
Patterns are merged with local state, not replaced. Conflicts are resolved by recency (newer wins).
bash# Read patterns from a sibling project on disk and republish under a new CID mcp tool call hooks_transfer --json -- '{"action": "from-project", "source": "/path/to/peer-project"}'
Useful for consolidating learnings across a monorepo or a fleet of related projects.
agentdb_consolidate does the local equivalent.aidefence_has_pii first) before publishing.agentdb_* export tools (out of scope here).ruflo-agentdb ADR-0001 §"Namespace convention" — defines pattern namespace that this transfer reads fromneural-train skill — produces the patterns that this skill ships| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 9,078 | 5,050 | -44% | 1 | 1 | 0% | 1,045 | 1,147 | +10% | 0 | 0 | — |
case-02 | fail→pass | 14,232 | 3,307 | -77% | 1 | 1 | 0% | 1,848 | 1,316 | -29% | 0 | 0 | — |
case-03 | fail→fail | 5,967 | 7,256 | +22% | 1 | 1 | 0% | 967 | 953 | -1% | 0 | 0 | — |
case-04 | fail→pass | 9,205 | 2,209 | -76% | 1 | 1 | 0% | 1,579 | 1,065 | -33% | 0 | 0 | — |
case-05 | fail→pass | 6,491 | 3,148 | -52% | 1 | 1 | 0% | 986 | 1,262 | +28% | 0 | 0 | — |
case-06 | fail→pass | 6,116 | 2,322 | -62% | 1 | 1 | 0% | 882 | 1,063 | +21% | 0 | 0 | — |
case-07 | fail→pass | 8,216 | 2,205 | -73% | 1 | 1 | 0% | 1,333 | 1,067 | -20% | 0 | 0 | — |
case-08 | fail→pass | 11,443 | 4,320 | -62% | 1 | 1 | 0% | 1,644 | 1,479 | -10% | 0 | 0 | — |
case-09 | fail→pass | 12,907 | 4,621 | -64% | 1 | 1 | 0% | 1,945 | 1,490 | -23% | 0 | 0 | — |
case-14 | fail→pass | 13,648 | 2,707 | -80% | 1 | 1 | 0% | 2,053 | 1,100 | -46% | 0 | 0 | — |
case-10 | fail→pass | 14,041 | 5,093 | -64% | 1 | 1 | 0% | 2,097 | 1,557 | -26% | 0 | 0 | — |
case-11 | fail→pass | 12,579 | 5,740 | -54% | 1 | 1 | 0% | 1,970 | 1,622 | -18% | 0 | 0 | — |
case-12 | pass→pass | 8,038 | 2,458 | -69% | 1 | 1 | 0% | 1,253 | 1,047 | -16% | 0 | 0 | — |
case-13 | fail→pass | 23,479 | 2,531 | -89% | 1 | 1 | 0% | 1,404 | 1,090 | -22% | 0 | 0 | — |
case-15 | fail→pass | 7,621 | 2,442 | -68% | 1 | 1 | 0% | 1,093 | 1,119 | +2% | 0 | 0 | — |
case-16 | fail→pass | 6,827 | 2,649 | -61% | 1 | 1 | 0% | 995 | 1,192 | +20% | 0 | 0 | — |
case-17 | pass→pass | 20,359 | 1,580 | -92% | 1 | 1 | 0% | 1,870 | 942 | -50% | 0 | 0 | — |
case-18 | fail→pass | 16,303 | 2,326 | -86% | 1 | 1 | 0% | 2,385 | 1,031 | -57% | 0 | 0 | — |
case-19 | pass→pass | 9,588 | 3,838 | -60% | 1 | 1 | 0% | 1,554 | 1,106 | -29% | 0 | 0 | — |
case-20 | fail→pass | 8,889 | 1,818 | -80% | 1 | 1 | 0% | 1,496 | 993 | -34% | 0 | 0 | — |
case-21 | fail→pass | 12,074 | 2,094 | -83% | 1 | 1 | 0% | 2,024 | 1,093 | -46% | 0 | 0 | — |
case-22 | pass→pass | 6,397 | 4,869 | -24% | 1 | 1 | 0% | 939 | 1,504 | +60% | 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 19 counted toward the lift figure. The other 3 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 +73 percentage points is the difference between those two pass rates over the 19 comparable cases.
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.