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aim-save

Save current session context to the AI Memory discussions collection.

41|5|Updated Jan 15, 2026
Search Tags:#developer tools#knowledge management#ai memory#context preservation#llm memory#session save
One-click install
npx skills add https://github.com/Hidden-History/ai-memory --skill aim-save
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aim-save
Source: https://github.com/Hidden-History/ai-memory/tree/main/.claude/skills/aim-save
Command: npx skills add https://github.com/Hidden-History/ai-memory --skill aim-save

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill allows users to manually save the current session's context and important decisions to the AI Memory system, ensuring that valuable information is preserved for future reference and doesn't need to be re-explained.

Core Features & Use Cases

  • Manual Session Saving: Explicitly store the current conversation state and key details.
  • Context Preservation: Ensures agents remember architectural decisions, project rules, and past interactions across sessions.
  • Use Case: Before ending a complex debugging session, use this Skill to save the problem, the steps taken, and the eventual solution, so you can pick up right where you left off next time.

Quick Start

Use the aim-save command to save the current session with a description of your progress.

Frequently Asked Questions about aim-save

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

FAQPage Schema
How do I save session context for LLM memory across different conversations?▼

You can save session context for LLM memory by using the aim-save command, which manually stores your current conversation state and key details into the AI Memory system's discussions collection.

What is the best way to preserve architectural decisions and project rules for AI agents?▼

The best way to preserve architectural decisions and project rules is through context preservation, which manually saves important decisions to AI Memory so agents remember past interactions across sessions.

How do I manually save a debugging session so I can resume it later?▼

To manually save a debugging session, use the aim-save command with a description of your progress; this captures the problem, steps taken, and solution as a structured summary with a timestamp.

Can I retrieve saved session context when starting a new AI conversation?▼

Yes, saved session context is retrievable by SessionStart or /aim-search, as the system stores entries with embeddings for semantic retrieval across future conversations.

Do I need a specific Python environment to store context to AI Memory?▼

Yes, storing context to AI Memory requires AI Memory services and a configured Python environment to process the structured summaries and generate embeddings for semantic retrieval.

What types of knowledge can I capture for future reference using session save?▼

Session save supports capturing type=session entries for general context, alongside agent_memory and agent_insight types for specific knowledge capture within the AI Memory system.

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