Memory Weaver Agent.
Extract user preferences and facts from chat streams, maintain persistent profiles, and inject relevant context into prompts.
Built for
What it does.
Memory Weaver builds long-term conversational profiles by scanning chat histories for actionable preferences and facts. It resolves contradictions, archives old values, and ignores transient noise to keep memory clean and lean.
The agent retrieves relevant context blocks on demand and injects them into system prompts—preserving token efficiency while ensuring AI assistants stay personalized across sessions. Works with semantic keyword matching and explicit conflict resolution rules.
Built for teams building virtual assistants, coaching bots, or any multi-turn agent that needs to remember what users actually want without cluttering the context window.
What’s inside.
Everything you need in the bundle. No tutorials. No assembly.
- 01Memory Profile schema and JSON structure for persistent user data storage
- 02Extraction rules that separate actionable preferences from conversational filler
- 03Contradiction resolution logic to handle conflicting user statements
- 04Context retrieval template for injecting memories into primary system prompts
- 05Edge case handling guidelines for hypothetical statements and profile bloat
- 06Python agent implementation showing preference extraction and prompt injection
- 07Workflow documentation covering ingestion, validation, querying, and injection
Drop it in. Press go.
- №01
Download
Buy once, get the bundle by email and on your dashboard.
- №02
Drop it in
Upload the files to your agent.
- №03
Connect
Wire up your tools with the setup notes.
- №04
Press go
The agent runs. You handle the people part.
About the creator.
Things people ask.
$29
Memory Weaver Agent.