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LautaroSanz
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mem-capture

Capture recent development work and decisions into persistent memory.

1|Updated Mar 12, 2026
Search Tags:#memory#persistence#ai assistant#development history#contextual recall#code capture
One-click install
npx skills add https://github.com/LautaroSanz/opencode-mem --skill mem-capture
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mem-capture
Source: https://github.com/LautaroSanz/opencode-mem/tree/main/.opencode/skills/mem-capture
Command: npx skills add https://github.com/LautaroSanz/opencode-mem --skill mem-capture

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill ensures that valuable development work, decisions, and insights are not lost at the end of a session, providing continuity and a searchable history for future reference.

Core Features & Use Cases

  • Persistent Memory: Captures recent work, code changes, and key decisions into a long-term memory system.
  • Contextual Recall: Enables future AI sessions to understand past work, aiding in debugging, feature development, and knowledge retention.
  • Use Case: After implementing a complex new feature, you can use this Skill to save a detailed summary, including the rationale, code changes, and potential pitfalls, ensuring that if you revisit the feature later or another developer needs to understand it, the context is readily available.

Quick Start

Use the mem-capture skill to save my recent work and decisions to memory.

Frequently Asked Questions about mem-capture

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

FAQPage Schema
How do I save AI assistant development history to persistent memory?▼

To save development history to persistent memory, you can use a capture tool that analyzes git status and diffs to extract code changes, categorize work, and save observations for future AI sessions.

What is the best way to retain code context and development decisions for future sessions?▼

Retaining code context involves capturing recent work into a persistent memory system that extracts key facts, files, and decisions, ensuring future AI sessions understand past development history.

How does contextual recall work for past code changes and bugfixes?▼

Contextual recall works by analyzing git diffs and categorizing work into features, bugfixes, or refactors, then saving these observations to provide a searchable history for future debugging.

Do I need a specific environment setup to capture git diffs into a persistent memory system?▼

Capturing git diffs into a persistent memory system requires a local development environment with git tracking enabled, allowing the tool to analyze status and extract code changes automatically.

Can I categorize development work like refactors and insights when saving to memory?▼

Yes, you can categorize development work when saving to memory, as the capture process automatically identifies work types like feature, bugfix, refactor, task, and insight before extracting key information.

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