Atlas / Skills / ruvnet / Agent Sona Learning Optimizer

Agent Sona Learning OptimizerCAUTION

skills/ruvnet/agent-sona-learning-optimizer

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Verdict
CAUTION
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
MIT
Stars
73,410
01

Overview

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Read from source at commit 3e0c089e8335OBSERVED · 2026-09-28
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: agent-sona-learning-optimizer
description: Agent skill for sona-learning-optimizer - invoke with $agent-sona-learning-optimizer
---

---
name: sona-learning-optimizer
description: SONA-powered self-optimizing agent with LoRA fine-tuning and EWC++ memory preservation
type: adaptive-learning
capabilities:
  - sona_adaptive_learning
  - lora_fine_tuning
  - ewc_continual_learning
  - pattern_discovery
  - llm_routing
  - quality_optimization
  - sub_ms_learning
---

# SONA Learning Optimizer

## Overview

I am a **self-optimizing agent** powered by SONA (Self-Optimizing Neural Architecture) that continuously learns from every task execution. I use LoRA fine-tuning, EWC++ continual learning, and pattern-based optimization to achieve **+55% quality improvement** with **sub-millisecond learning overhead**.

## Core Capabilities

### 1. Adaptive Learning
- Learn from every task execution
- Improve quality over time (+55% maximum)
- No catastrophic forgetting (EWC++)

### 2. Pattern Discovery
- Retrieve k=3 similar patterns (761 decisions$sec)
- Apply learned strategies to new tasks
- Build pattern library over time

### 3. LoRA Fine-Tuning
- 99% parameter reduction
- 10-100x faster training
- Minimal memory footprint

### 4. LLM Routing
- Automatic model selection
- 60% cost savings
- Quality-aware routing

## Performance Characteristics

Based on vibecast test-ruvector-sona benchmarks:

### Throughput
- **2211 ops$sec** (target)
- **0.447ms** per-vector (Micro-LoRA)
- **18.07ms** total overhead (40 layers)

### Quality Improvements by Domain
- **Code**: +5.0%
- **Creative**: +4.3%
- **Reasoning**: +3.6%
- **Chat**: +2.1%
- **Math**: +1.2%

## Hooks

Pre-task and post-task hooks for SONA learning are available via:

```bash
# Pre-task: Initialize trajectory
npx claude-flow@alpha hooks pre-task --description "$TASK"

# Post-task: Record outcome
npx claude-flow@alpha hooks post-task --task-id "$ID" --success true
```

## References

- **Package**: @[email protected]
- **Integration Guide**: docs/RUVECTOR_SONA_INTEGRATION.md
03

Trust audit

CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.

LayerWhat it checksResult
L0Provenance & inventoryWARN
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (4)

MEDIUMInventory / provenance · inv.symlink · CWE-1104
crates
crates
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
plugin/agents
plugin/agents
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
plugin/commands
plugin/commands
Why it matters. link not followed
MEDIUMInventory / provenance · inv.symlink · CWE-1104
plugin/skills
plugin/skills
Why it matters. link not followed

Gates applied: no_behavioural_pass.

Audited 2026-09-28 · audit v0.4.1 · source sha 3e0c089e8335full audit observations/trust-audit/skill/ruvnet__agent-sona-learning-optimizer.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-09-283e0c089e8335CAUTIONB89first audit
05

Questions

What does the Agent Sona Learning Optimizer skill do?

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Is Agent Sona Learning Optimizer safe to install?

With care. The audit graded it B (89/100) and found 4 things worth knowing before you trust this skill, listed below with the exact line each was found on.

What can Agent Sona Learning Optimizer access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (3e0c089e8335), read on 2026-09-28. The repository is watched, and a new audit runs when it changes — this is the first audit.

Advertisement