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AgentDB Memory Patterns - Persistent memory patterns for AI agents using AgentDB.

Implement persistent memory patterns for AI agents using AgentDB, including session memory, long-term storage, pattern learning, and context management.

Tags

Updated: 2026-09-20
agent-memoryagentdbvector-databasereasoningbankcontext-management

Capabilities

Initialize AgentDB databaseStore session and fact memoriesRetrieve context with reasoningConsolidate and optimize agent memory

Typical Inputs

Query vector embeddingsSession data and message contentConfiguration options

Typical Outputs

Persistent database filesSynthesized context and retrieved patternsJSON vector backup files

What this skill does

  • Initialize AgentDB database
  • Store session and fact memories
  • Retrieve context with reasoning
  • Consolidate and optimize agent memory
  • Migrate legacy ReasoningBank database
  • Export and import database vectors

Inputs

  • Query vector embeddings
  • Session data and message content
  • Configuration options
  • Legacy database files
  • JSON vector backup files

Outputs

  • Persistent database files
  • Synthesized context and retrieved patterns
  • JSON vector backup files
  • Database statistics and benchmark metrics

Requirements

  • Node.js 18+
  • AgentDB v1.0.7+

Source

  • Spec: SKILL.md

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