
Intelligence Transfer
FreeShare learned patterns across projects using IPFS.
Free · Opens the source repo
What Intelligence Transfer does
Intelligence Transfer is a skill designed for developers and teams working on machine learning projects that require knowledge sharing across different environments. By utilizing IPFS (InterPlanetary File System) and Pinata, this skill allows users to publish and fetch learned patterns from one project to another. This cross-project sharing is particularly useful for teams that want to leverage previous learnings to accelerate the development of new projects or improve existing ones.
The process begins with the ability to publish the current project's patterns to IPFS. Users can inspect their locally stored patterns and then publish them, receiving a content identifier (CID) that can be shared with peers. This CID serves as a reference point for others to access the same patterns, effectively creating a deploy artifact for the learned intelligence of the agents involved.
Intelligence Transfer is especially beneficial in scenarios where a fresh project is initiated. By fetching relevant patterns from a parent project, new agents can start with prior knowledge, minimizing the learning curve. Additionally, after achieving major milestones, teams can publish their patterns to benefit other projects, fostering a culture of collaboration and shared learning. This skill is also useful during debugging phases, allowing teams to pull known-good patterns for comparison.
However, it is important to note that this skill is not intended for daily use due to the overhead associated with fetching and publishing patterns. For routine operations, a local equivalent like agentdb_consolidate is recommended. Moreover, users should be cautious about publishing sensitive information, as IPFS is public by default, and patterns should be stripped of PII before being shared.
When to use it
Use this skill when starting a new project to leverage existing patterns or after significant learning milestones to share insights with peers.
When not to use it
Avoid using this skill for daily operations or when handling sensitive patterns due to IPFS's public nature.
What you can build with it
Starting a New Project
Fetch relevant patterns from a parent project to give new agents prior knowledge, speeding up the onboarding process.
Sharing After Milestones
Publish learned patterns after significant achievements to benefit other projects and teams.
Debugging Issues
Retrieve a known-good pattern set to compare against current project patterns during regression debugging.
How to install Intelligence Transfer
View source1. Install with the skills CLI
npx skills add ruvnet/ruflo/intelligence-transfer --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by ruvnetIntelligence 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_consolidatedoes the local equivalent. - For sensitive patterns — IPFS is public by default. Pinata pinning does NOT make patterns private. Strip PII (use
aidefence_has_piifirst) 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-agentdbADR-0001 §"Namespace convention" — definespatternnamespace that this transfer reads fromneural-trainskill — produces the patterns that this skill ships
Frequently asked questions about Intelligence Transfer
Similar skills
Skill Creator
Efficiently create and manage skills for Gemini CLI.
Agent Development
Create and manage autonomous agents for Claude Code.
Math Olympiad Solver
Solve and verify competition math problems effectively.
Microsoft Skill Creator
Create specialized skills for Microsoft technologies.
Doublecheck
A verification pipeline for AI-generated claims.
Skill Development for Claude Code
Create and enhance skills for Claude Code plugins.
