AgentsAvançado

Memory Evolution

pornhadaututtheky·nhadaututtheky· v1.0.0 · atualizado em 2026-04-10

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This skill enables the AI agent to evolve its memory over time. It allows for continuous learning and adaptation by refining and updating stored information based on new experiences and feedback.

memory-managementknowledge-optimizationneural-memoryagent-performancememory-evolutionrecall-improvement

Linguagens

multi-language

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Documento do Skill

SKILL.mdmemory-evolution/workflow

Usage Pattern Discovery: — Analyze memory access patterns and recall quality.

Bottleneck Analysis: — Identify and score bottlenecks in memory recall.

Evolution Actions: — Propose and execute memory optimization actions (consolidation, enrichment, pruning, etc.).

Checkpoint: — Record the evolution cycle and gather user feedback.

Metrics Report: — Generate a report on the impact of the evolution cycle.

Telemetria de Agentes

Execuções

total

Taxa de Sucesso

últimos 30d

Latência Média

0.0s

p50

Alucinação

0.0%

detecção

Tokens Entrada

avg 0/exec

Tokens Saída

avg 0/exec

Uso por Plataforma

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Árvore do Skill

Memory Evolution

memory-evolution

Fases Cognitivas7

1.SENSE

2.CONTEXTUALIZE

3.HYPOTHESIZE

4.EVALUATE

5.RECOMMEND

6.ACT

7.REFLECT

Triggers8

analyze memory usage patternsoptimize agent memoryimprove recall qualityrun memory evolution cycleidentify memory bottlenecksconsolidate fragmented memoriesprune irrelevant memoriesenrich incomplete memories

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Score Breakdown

⭐Avaliação Humana0%

🤖Sucesso de Agentes0%

🕐Atualidade100%

🔗Saúde de Dependências100%

🕸️Centralidade no Grafo0%

🛡️Segurança50%

CompositeScore = α·Humano + β·Agente + γ·Recência + δ·Deps + ε·Centralidade + ζ·Segurança

Instalação

$ synaptic mcp download memory-evolution

$ synaptic skills detail memory-evolution

$ synaptic skills live memory-evolution

Links

GitHub Repository