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ehfazrezwan
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save-session

Extract and persist session facts and decisions to structured memory.

5|1|Updated Feb 10, 2026
Search Tags:#claude-code#cross-session#claude-cowork#memory-capture#session-save#neuralscape#conversation-facts
One-click install
npx skills add https://github.com/ehfazrezwan/neuralscape --skill save-session-ehfazrezwan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: save-session
Source: https://github.com/ehfazrezwan/neuralscape/tree/main/neuralscape-plugin/skills/save-session
Command: npx skills add https://github.com/ehfazrezwan/neuralscape --skill save-session-ehfazrezwan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the risk of losing valuable conversation context, key decisions, and durable facts when a working session ends, ensuring critical knowledge is preserved for future sessions without manual rework.

Core Features & Use Cases

  • Dual Extraction Paths: Choose between the fast checkpoint path for user-distilled facts and structured session notes, or the remember_conversation path for server-side LLM extraction from raw session transcripts.
  • Automatic Scoping: Resolves project and user identities automatically using environment variables, project markers, and git repository metadata to ensure memories are stored in the correct context.
  • Use Case: After a 3-hour debugging session where you identified a flaky API endpoint and agreed on a new retry policy, use this Skill to save those facts so the next session immediately picks up the context without re-explaining the issue.

Quick Start

Use the save-session skill to persist all durable facts and key decisions from your current working conversation to Neuralscape memory.

Frequently Asked Questions about save-session

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

FAQPage Schema
How do I save conversation context and key decisions from Claude Code for future sessions?▼

To save conversation context, the session facts are extracted and persisted to a structured long-term memory layer. This ensures durable facts and key decisions are retained across sessions without manual rework or re-explaining previous issues.

What is the best way to retain AI coding assistant context after a long debugging session?▼

Retaining AI coding assistant context involves capturing durable facts at session end to a long-term memory layer. You can use a fast checkpoint path for user-distilled facts or rely on server-side extraction from raw conversation transcripts.

Does this session memory capture tool support automatic deduplication and project scoping?▼

Session memory capture supports automatic deduplication and project scoping. It resolves project and user identities automatically using environment variables, project markers, and git repository metadata to store memories in the correct context.

Can I extract session facts automatically from raw conversation transcripts?▼

You can extract session facts automatically from raw conversation transcripts using the remember_conversation path. This enables server-side LLM extraction to identify and persist durable facts without requiring manually user-distilled fact sets.

How do cross-session memory tools handle user identity resolution for async storage?▼

Cross-session memory tools handle user identity resolution by resolving project and user identities automatically using environment variables and git metadata. This satisfies async memory storage requirements to ensure correct project scoping for knowledge retention.

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