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agent-v3-memory-specialist

Agent skill for v3-memory-specialist - invoke with $agent-v3-memory-specialist

Install with Tessl CLI

npx tessl i github:ruvnet/claude-flow --skill agent-v3-memory-specialist
What are skills?

31

Does it follow best practices?

Validation for skill structure

SKILL.md
Review
Evals

Evaluation results

73%

20%

Unified Memory Search Module

HNSW indexing and query routing

Criteria
Without context
With context

HNSW dimensions

0%

100%

HNSW efConstruction

100%

100%

HNSW M parameter

100%

100%

HNSW maxElements

0%

100%

Semantic query routing

100%

100%

Structured query routing

50%

60%

Dual store write

100%

70%

IMemoryBackend interface

0%

0%

MemoryEntry embedding field

80%

100%

AgentDBAdapter usage

0%

0%

Without context: $0.5677 · 2m 58s · 21 turns · 27 in / 11,230 out tokens

With context: $2.0589 · 7m 24s · 68 turns · 509 in / 22,263 out tokens

96%

34%

Agent Memory Migration

Legacy backend migration to AgentDB

Criteria
Without context
With context

SQLite field extraction

100%

100%

SQLite embedding generation

100%

100%

Markdown originalFile metadata

0%

100%

Markdown migrationDate metadata

0%

100%

Markdown type metadata

0%

100%

Markdown embedding generation

100%

100%

AgentDB as target

0%

100%

Phased migration plan

100%

100%

Backward compatibility

100%

100%

MemoryEntry structure

100%

50%

Order by created_at

100%

100%

Without context: $0.9842 · 4m 12s · 43 turns · 50 in / 13,487 out tokens

With context: $1.8546 · 7m 3s · 65 turns · 69 in / 19,540 out tokens

87%

56%

Adaptive Learning Pattern Store

SONA pattern storage and benchmarking

Criteria
Without context
With context

sonaMode field present

0%

100%

Valid sonaMode values

0%

100%

reward metadata field

100%

100%

trajectory metadata field

0%

100%

adaptation_time metadata field

0%

100%

Semantic retrieval query type

0%

37%

Retrieval filter by type

0%

50%

Retrieval limit: 5

100%

100%

Benchmark 1000 queries

0%

100%

Benchmark queriesPerSecond

100%

100%

Benchmark avgLatency

50%

70%

Without context: $0.8755 · 3m 55s · 36 turns · 43 in / 14,136 out tokens

With context: $1.0550 · 4m 41s · 34 turns · 38 in / 16,985 out tokens

Evaluated
Agent
Claude Code

Table of Contents

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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.