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ehfazrezwan
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neuralscape-adapter

Map custom AI agent event formats to NeuralScape conversation schemas.

5|1|Updated Feb 10, 2026
Search Tags:#adapter development#memory system#conversation capture#neuralscape#agent framework integration#plugin extension#AI client adapter
One-click install
npx skills add https://github.com/ehfazrezwan/neuralscape --skill neuralscape-adapter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: neuralscape-adapter
Source: https://github.com/ehfazrezwan/neuralscape/tree/main/.claude/skills/neuralscape-adapter
Command: npx skills add https://github.com/ehfazrezwan/neuralscape --skill neuralscape-adapter

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill solves the gap of unsupported AI agent frameworks in NeuralScape's conversation capture system, enabling developers to add persistent memory support for custom AI coding assistants, niche tools, and internal agent platforms that are not natively compatible.

Core Features & Use Cases

  • Custom Adapter Development: Step-by-step guidance to build adapters that map new AI client event formats to NeuralScape's standard conversation turn schema.
  • Pipeline Integration: Covers client detection logic, hook manifest configuration, and build validation to ensure new adapters work seamlessly with NeuralScape's existing memory processing pipeline.
  • Use Case: A developer using a custom internal AI coding agent can use this Skill to build an adapter that captures conversation turns from the agent and stores them in NeuralScape's vault, matching the functionality of natively supported tools like Claude Code and Cursor.

Quick Start

Use the neuralscape-adapter skill to create and register a custom adapter for your new AI agent framework to integrate it with NeuralScape's conversation capture and memory storage pipeline.

Frequently Asked Questions about neuralscape-adapter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I integrate a custom AI agent framework with a memory system for conversation capture?▼

To integrate a custom AI agent framework for conversation capture, you build an adapter that maps the client's event formats to a standard conversation turn schema. This enables persistent memory storage within an existing pipeline.

What is an AI client adapter for persistent memory systems?▼

An AI client adapter is a bridge that translates arbitrary event formats from third-party agents into standard conversation turns. It allows non-native coding assistants to utilize a unified hook system for memory capture.

How do I map custom agent events to a standard conversation turn schema?▼

You map custom agent events to a standard conversation turn schema by developing a custom adapter. This process involves configuring client detection logic and hook manifests to align with the memory processing pipeline.

Can I add persistent memory support for internal AI coding assistants not officially supported?▼

Yes, you can add persistent memory support for unsupported internal AI coding assistants. By developing a custom adapter, you capture conversation turns and store them in the vault, matching natively supported tools.

What is the best way to extend a unified conversation hook system to new AI tools?▼

The best way to extend a unified conversation hook system is creating a custom adapter. This maps new client-specific event formats to standard schemas, integrating seamlessly with existing turn flushing and session compilation.

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