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Provide secure local cognition, memory, and multi-agent orchestration for AI agents.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "prism-coder" yet — see the docs or source repo.
Using prism-coder, design a locally running AI agent setup with persistent memory, no API keys, and suitability for sensitive medical text. Provide the architecture and deployment steps.
A local AI agent implementation plan covering architecture, privacy and security considerations, and deployment steps.
Use prism-coder to design a multi-agent Hivemind workflow where a research agent handles retrieval, an analysis agent synthesizes findings, and a review agent performs adversarial evaluation. Explain how memory is shared across agents.
A clear multi-agent workflow with role definitions, task handoffs, shared memory design, and quality control.
Create a test plan for prism-coder to validate persistent memory performance, ACT-R activation behavior, and how adversarial evaluation reduces hallucinations and faulty reasoning.
A test plan with metrics, experimental methods, evaluation cases, and criteria for judging results.
Give AI coding agents local-first persistent memory for more consistent development.
Give AI coding agents persistent cross-session memory for project knowledge.
Give AI coding agents persistent memory across sessions for people, decisions, and context.
Keep AI coding agents architecture-aware, verified, drift-checked, and safer over long tasks.
Provide durable, local-first memory for AI coding agents across MCP hosts.
Give AI coding agents persistent cross-project memory and connected context retrieval.