agent-safla-neural
Agent skill for safla-neural - invoke with $agent-safla-neural
36
0%
Does it follow best practices?
Impact
100%
3.03xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agents/skills/agent-safla-neural/SKILL.mdEvaluation results
100%
38%AI Memory System Architecture
Four-tier memory architecture design
Vector Memory named
0%
100%
Episodic Memory named
100%
100%
Semantic Memory named
100%
100%
Working Memory named
100%
100%
Vector retrieval method
0%
100%
Vector cross-domain
0%
100%
Episodic history
100%
100%
Episodic temporal
100%
100%
Semantic factual
100%
100%
Working Memory scope
100%
100%
All four tiers present
0%
100%
100%
81%Multi-Agent Coordination Neural Training Setup
Neural training MCP initialization
Correct MCP function
26%
100%
pattern_type coordination
0%
100%
safla-transformer architecture
0%
100%
memory_tiers vector
0%
100%
memory_tiers episodic
0%
100%
memory_tiers semantic
0%
100%
memory_tiers working
0%
100%
feedback_loops enabled
0%
100%
persistence enabled
0%
100%
epochs count
100%
100%
100%
82%AI Interaction Pattern Logger
Memory pattern storage MCP call
Correct MCP function
0%
100%
action store
0%
100%
Correct namespace
0%
100%
Key prefix pattern
0%
100%
Key includes timestamp
100%
100%
Value context field
0%
100%
Value outcome field
0%
100%
Value learning field
0%
100%
Value confidence field
100%
100%
TTL 604800
0%
100%
- Repository
- ruvnet/claude-flow
- Commit
f547cec
- Evaluated
- Agent
- Claude Code
- Model
- Claude Sonnet 4.6
Table of Contents
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