mirror of
https://github.com/ruvnet/ruflo.git
synced 2026-10-23 03:47:00 +09:00
Reuvenandclaude-flow
81418649c6
Complete plugin marketplace for Ruflo with validated Claude Code plugin format: - ruflo-core: MCP server, status, doctor, plugin discovery - ruflo-swarm: swarm coordination, Monitor, worktree isolation - ruflo-autopilot: autonomous /loop completion with learning - ruflo-intelligence: SONA neural patterns, trajectory learning, routing - ruflo-agentdb: AgentDB controllers, HNSW vector search, RuVector - ruflo-aidefence: AI safety scanning, PII detection, prompt defense - ruflo-browser: Playwright browser automation, testing, scraping - ruflo-jujutsu: git diff analysis, risk scoring, reviewer recs - ruflo-wasm: sandboxed WASM agents and gallery sharing - ruflo-workflows: workflow templates, orchestration, lifecycle - ruflo-daa: Dynamic Agentic Architecture, cognitive patterns - ruflo-ruvllm: local LLM inference, MicroLoRA, SONA, chat format - ruflo-rvf: RVF portable memory, session persistence, transfer - ruflo-loop-workers: background /loop workers, CronCreate - ruflo-security-audit: CVE scanning, dependency checks - ruflo-rag-memory: simple store/search/recall interface - ruflo-testgen: test gap detection, TDD workflow - ruflo-docs: doc generation, drift detection - ruflo-plugin-creator: scaffold, validate, publish new plugins All 19 pass `claude plugin validate`. Skills auto-discovered from directory structure (not declared in plugin.json). Each skill wires to ruflo MCP tools via allowed-tools frontmatter. Includes: marketplace.json, GitHub Pages storefront, CI validation workflow, minimalist README with USERGUIDE split. Co-Authored-By: claude-flow <ruv@ruv.net>
1.5 KiB
1.5 KiB
name, description, allowed-tools
| name | description | allowed-tools |
|---|---|---|
| llm-config | Configure RuVLLM local inference with model selection, MicroLoRA fine-tuning, and SONA adaptation | mcp__claude-flow__ruvllm_generate_config mcp__claude-flow__ruvllm_status mcp__claude-flow__ruvllm_microlora_create mcp__claude-flow__ruvllm_microlora_adapt mcp__claude-flow__ruvllm_sona_create mcp__claude-flow__ruvllm_sona_adapt Bash |
LLM Configuration
Configure RuVLLM for local inference and fine-tuning.
When to use
When you need to configure local LLM inference, create MicroLoRA adapters for task-specific fine-tuning, or set up SONA for real-time adaptation.
Steps
- Check status — call
mcp__claude-flow__ruvllm_statusto see current model and adapter state - Generate config — call
mcp__claude-flow__ruvllm_generate_configwith model parameters - Create MicroLoRA — call
mcp__claude-flow__ruvllm_microlora_createfor task-specific adapters - Adapt MicroLoRA — call
mcp__claude-flow__ruvllm_microlora_adaptwith training data - Create SONA — call
mcp__claude-flow__ruvllm_sona_createfor real-time neural adaptation - Adapt SONA — call
mcp__claude-flow__ruvllm_sona_adaptwith feedback signals
MicroLoRA vs SONA
| Feature | MicroLoRA | SONA |
|---|---|---|
| Speed | Minutes to train | <0.05ms adaptation |
| Scope | Task-specific fine-tuning | Real-time micro-adjustments |
| Persistence | Saved as adapter weights | Session-scoped |
| Use case | Specialized domain tasks | Continuous feedback loops |