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AI/ML · Global library

Agent Memory Designer

Design short-term, long-term, and episodic memory layers for agents without turning retrieval into an unbounded context leak.

CodexClaude CodeKimi Codeorchestrator-mcp
Open pack on GitHubBack to catalog

Best use case

Use Agent Memory Designer when you need to design short-term, long-term, and episodic memory layers for agents without turning retrieval into an unbounded context leak, especially when the work is driven by agent memory and episodic recall.

Trigger signals

agent memoryepisodic recallcontext retrieval

Validation hooks

memory-retrieval-checkercontext-relevance-validatorforgetting-curve-test

Install surface

Copy the exact command path you need.

Inspect

pip install "orchestrator-mcp[dashboard]"
orchestrator-mcp skills show agent-memory-designer

Use

orchestrator-mcp skills export agent-memory-designer --to ./skillforge-packs
# copy the exported pack into your preferred agent environment

Export

cp -R skills/agent-memory-designer ./your-agent-skills/agent-memory-designer
# or open skills/agent-memory-designer/SKILL.md in a markdown-first client

File patterns

**/*.py**/*.ts**/memory/****/agents/**

Model preferences

moonshotai/kimi-k2.5deepseek-ai/deepseek-v3.2deepseek-r1:32b

Related skills

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Manage complete agent lifecycles from initialization through graceful shutdown with health monitoring, scaling, and resource optimization

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Agent Swarm Optimizer

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Optimize large-scale agent swarms for emergent problem-solving with dynamic task allocation and collective intelligence patterns

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Apache-2.0 licensedUse it, fork it, redistribute it. No strings attached.Safety-first by designSecret redaction, release scanning, and no shell execution. Constraints are public.GitHub nativeEvery pack is a real folder. Fork, edit, PR. No hidden backend or proprietary pipeline.