📦 Pattern Store & Export

/intelligence--learning/pattern-store--export

Share learned patterns across projects, teams, and the community via the decentralized pattern marketplace.

Asset Type	Description	Use Case
Patterns	Learned strategies from ReasoningBank	Share what works across projects
Agent Configs	Optimized YAML configurations	Pre-tuned agents for specific domains
Workflows	Multi-step task templates	Reusable automation sequences
Embeddings	Pre-computed vector indexes	Skip bootstrap time on new projects
Hooks	Custom hook implementations	Extend system behavior

Export Commands

bash

npx ruflo@latest memory export --format json --output ./patterns.json

npx ruflo@latest memory export --namespace "security" --output ./security-patterns.json

npx ruflo@latest memory export --include-embeddings --output ./full-export.json

npx ruflo@latest config export --scope project --output ./agent-configs.json

npx ruflo@latest session export --session-id "my-session" --output ./session.json

Import Commands

bash

npx ruflo@latest memory import --input ./patterns.json

npx ruflo@latest memory import --input ./patterns.json --merge

npx ruflo@latest hooks transfer --source-path ../other-project

npx ruflo@latest config import --input ./agent-configs.json --scope project

npx ruflo@latest session restore --session-id "my-session"

Pattern Store (IPFS Marketplace)

Decentralized pattern marketplace for sharing and discovering community patterns.

Command	Description
`transfer-store search`	Search patterns by keyword, category, or rating
`transfer-store info`	Get detailed info about a pattern
`transfer-store download`	Download pattern with integrity verification
`transfer-store publish`	Publish your patterns to the store
`transfer-store featured`	Browse featured/curated patterns
`transfer-store trending`	See what's popular

bash

npx ruflo@latest transfer-store search --query "authentication" --min-rating 4.0

npx ruflo@latest transfer-store download --id "auth-jwt-patterns-v2" --verify

npx ruflo@latest transfer-store publish --input ./my-patterns.json --category "security"

Plugin Store

Discover and install community plugins from the live IPFS registry with 19 official plugins and live ratings via Cloud Function.

Command	Description
`plugins list`	List available plugins with live ratings
`plugins rate`	Rate a plugin (1-5 stars)
`transfer plugin-search`	Search plugins by type or category
`transfer plugin-info`	Get plugin details and dependencies
`transfer plugin-featured`	Browse featured plugins
`transfer plugin-official`	List official/verified plugins

bash

npx ruflo@latest plugins list

npx ruflo@latest plugins list --type integration

npx ruflo@latest plugins rate --name @claude-flow/embeddings --rating 5

npx ruflo@latest transfer plugin-search --type "mcp-tool" --verified

npx ruflo@latest transfer plugin-info --name "semantic-code-search"

npx ruflo@latest transfer plugin-official

Live IPFS Plugin Registry

The official plugin registry is hosted on IPFS with Ed25519 signature verification:

Property	Value
Live CID	`bafkreiahw4ufxwycbwwswt7rgbx6hkgnvg3rophhocatgec4bu5e7tzk2a`
Plugins	19 official plugins
Verification	Ed25519 signed registry
Gateways	Pinata, ipfs.io, dweb.link, Cloudflare

bash

curl -s "https://gateway.pinata.cloud/ipfs/bafkreiahw4ufxwycbwwswt7rgbx6hkgnvg3rophhocatgec4bu5e7tzk2a"

IPFS Integration

Patterns and models are distributed via IPFS for decentralization and integrity.

Feature	Benefit
Content Addressing	Patterns identified by hash, tamper-proof
Decentralized	No single point of failure
Ed25519 Signatures	Cryptographic registry verification
Multi-Gateway	Automatic failover (Pinata, ipfs.io, dweb.link)
PII Detection	Automatic scanning before publish

bash

npx ruflo@latest transfer ipfs-resolve --name "/ipns/patterns.ruflo.io"

npx ruflo@latest transfer detect-pii --content "$(cat ./patterns.json)"

Model & Learning Pattern Import/Export

Share trained neural patterns and learning models via IPFS.

Operation	Description
Export	Pin learning patterns to IPFS, get shareable CID
Import	Fetch patterns from any IPFS CID
Analytics	Track downloads and sharing metrics

bash

curl -X POST "https://api.pinata.cloud/pinning/pinJSONToIPFS" \
  -H "Authorization: Bearer $PINATA_JWT" \
  -d '{
    "pinataContent": {
      "type": "learning-pattern",
      "name": "my-patterns",
      "patterns": [...]
    },
    "pinataMetadata": {"name": "ruflo-learning-pattern"}
  }'

curl -s "https://gateway.pinata.cloud/ipfs/QmYourCIDHere"

curl "https://publish-registry-xxx.cloudfunctions.net?action=export-model" -d @model.json
curl "https://publish-registry-xxx.cloudfunctions.net?action=import-model&cid=QmXxx"

Supported Model Types

Type	Description	Use Case
`learning-pattern`	Agent learning patterns	Code review, security analysis
`neural-weights`	Trained neural weights	SONA, MoE routing
`reasoning-bank`	Reasoning trajectories	Few-shot learning
`agent-config`	Agent configurations	Swarm templates

Pre-trained Model Registry

Import pre-defined rule-based patterns for common tasks. 40 patterns across 8 categories (trigger-action rules, not ML-trained models).

Model	Category	Patterns	Accuracy	Use Case
`security-review-patterns`	security	5	94%	SQL injection, XSS, path traversal
`code-review-patterns`	quality	5	90%	SRP, error handling, type safety
`performance-optimization-patterns`	performance	5	89%	N+1 queries, memory leaks, caching
`testing-patterns`	testing	5	91%	Edge cases, mocking, contracts
`api-development-patterns`	api	5	92%	REST conventions, validation, pagination
`bug-fixing-patterns`	debugging	5	89%	Null tracing, race conditions, regressions
`refactoring-patterns`	refactoring	5	89%	Extract methods, DRY, value objects
`documentation-patterns`	documentation	5	90%	JSDoc, OpenAPI, ADRs

Registry CID: QmNr1yYMKi7YBaL8JSztQyuB5ZUaTdRMLxJC1pBpGbjsTc

bash

curl -s "https://gateway.pinata.cloud/ipfs/QmNr1yYMKi7YBaL8JSztQyuB5ZUaTdRMLxJC1pBpGbjsTc" | jq '.models[].name'

npx ruflo@latest transfer import --cid QmNr1yYMKi7YBaL8JSztQyuB5ZUaTdRMLxJC1pBpGbjsTc

npx ruflo@latest neural import --model security-review-patterns --source ipfs

npx ruflo@latest hooks route --task "review authentication code" --use-patterns

Benefits vs Fresh Install

Metric	Fresh Install	With Pre-trained
Patterns Available	0	40
Detection Patterns	~50-60%	40 rule-based patterns
Pattern Categories	0	8 categories
Issue Detection Rate	~60-70%	~90-95%
Time to First Insight	Discovery needed	Immediate

Pre-Built Pattern Packs

Pack	Patterns	Best For
security-essentials	45	Auth, validation, CVE patterns
testing-patterns	32	TDD, mocking, fixture strategies
performance-optimization	28	Caching, query optimization
api-development	38	REST, GraphQL, error handling
devops-automation	25	CI/CD, deployment, monitoring

bash

npx ruflo@latest transfer-store download --id "security-essentials" --apply

RuVector WASM Neural Training

Real WASM-accelerated neural training using @ruvector/learning-wasm and @ruvector/attention packages for state-of-the-art performance.

Component	Performance	Description
MicroLoRA	<3μs adaptation	Rank-2 LoRA with 105x faster than 100μs target
ScopedLoRA	17 operators	Per-task-type learning (coordination, security, testing)
FlashAttention	9,127 ops/sec	Memory-efficient attention mechanism
TrajectoryBuffer	10k capacity	Success/failure learning from patterns
InfoNCE Loss	Contrastive	Temperature-scaled contrastive learning
AdamW Optimizer	β1=0.9, β2=0.999	Weight decay training optimization

bash

npx ruflo@latest neural list

npx ruflo@latest neural list --category security

npx ruflo@latest neural train -p coordination -e 100 --wasm --flash --contrastive

npx ruflo@latest neural train -p security --wasm --contrastive

npx ruflo@latest neural benchmark -d 256 -i 1000

npx ruflo@latest neural import --cid QmNr1yYMKi7YBaL8JSztQyuB5ZUaTdRMLxJC1pBpGbjsTc

npx ruflo@latest neural export --ipfs --sign

Benchmark Results

+---------------------+---------------+-------------+
| Mechanism           | Avg Time (ms) | Ops/sec     |
+---------------------+---------------+-------------+
| DotProduct          | 0.1063        | 9,410       |
| FlashAttention      | 0.1096        | 9,127       |
| MultiHead (4 heads) | 0.1661        | 6,020       |
| MicroLoRA           | 0.0026        | 383,901     |
+---------------------+---------------+-------------+
MicroLoRA Target (<100μs): ✓ PASS (2.60μs actual)

Training Options

Flag	Description	Default
`--wasm`	Enable RuVector WASM acceleration	`true`
`--flash`	Use Flash Attention	`true`
`--moe`	Enable Mixture of Experts routing	`false`
`--hyperbolic`	Hyperbolic attention for hierarchical patterns	`false`
`--contrastive`	InfoNCE contrastive learning	`true`
`--curriculum`	Progressive difficulty curriculum	`false`
`-e, --epochs`	Number of training epochs	`50`
`-d, --dim`	Embedding dimension (max 256)	`256`
`-l, --learning-rate`	Learning rate	`0.01`

🪝 Hooks, Event Hooks, Workers & Pattern Intelligence

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