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intelligence-transfer

Publish or fetch learned patterns across projects via IPFS (Pinata) -- the cross-project pattern transfer that hooks_transfer enables

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Intelligence Transfer

Cross-project pattern sharing via IPFS. Lets a different project — or a different machine — fetch and apply patterns this project has already learned.

Why this exists

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."

Prerequisite

# 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.

Workflows

Publish current project's patterns

# 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.

Fetch + apply a peer's patterns

# 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).

Mirror an entire project's patterns

# 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.

When to use this skill

  • Before a fresh project starts — fetch the relevant patterns from a parent project so the new project's agents start with prior knowledge instead of cold.
  • After a major learning milestone — publish so other projects benefit.
  • When debugging a regression — fetch a known-good pattern set to compare against.

When NOT to use

  • Daily — it's a heavyweight operation. agentdb_consolidate does the local equivalent.
  • For sensitive patterns — IPFS is public by default. Pinata pinning does NOT make patterns private. Strip PII (use aidefence_has_pii first) before publishing.

Caveats

  • IPFS CIDs are content-addressed; republishing the same pattern set gives you the same CID.
  • Patterns are stored as JSON; they include only the embedding hashes + metadata, not raw text. Decoding requires the same SONA / MicroLoRA adapter version that produced them.
  • This skill does NOT publish AgentDB rows — only the intelligence-side patterns. To ship full memory, use agentdb_* export tools (out of scope here).

Related

  • ruflo-agentdb ADR-0001 §"Namespace convention" — defines pattern namespace that this transfer reads from
  • neural-train skill — produces the patterns that this skill ships

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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