mcp-memory-first-development

Synchronize short-term project memories with long-term design knowledge across development workflows.

1|Updated May 3, 2024
One-click install
npx skills add https://github.com/NEXTAltair/LoRAIro --skill mcp-memory-first-development
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: mcp-memory-first-development
Source: https://github.com/NEXTAltair/LoRAIro/tree/main/.claude/skills/mcp-memory-first-development
Command: npx skills add https://github.com/NEXTAltair/LoRAIro --skill mcp-memory-first-development

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill tackles the challenge of maintaining context, recalling past decisions, and documenting knowledge throughout the development lifecycle. It integrates short-term progress tracking with long-term design knowledge, ensuring efficient, consistent, and well-documented development.

Core Features & Use Cases

  • Dual-Memory Strategy: Combines Serena's rapid, short-term project notes with Cipher's persistent, searchable design knowledge for comprehensive context.
  • Pre-Implementation Review: Quickly access past solutions and project status before starting new tasks, avoiding redundant work and leveraging existing expertise.
  • Continuous Progress Tracking: Record ongoing decisions, challenges, and next steps, making interruptions seamless and project handovers smooth.
  • Knowledge Accumulation: Systematically store design rationale, technical choices, and lessons learned for future reference, building a valuable organizational asset.
  • Use Case: When picking up a task after a break, use read_memory to instantly recall your last stopping point and cipher_memory_search to review relevant design patterns, then write_memory to log your progress.

Quick Start

Example: Check current project status

mcp__serena__read_memory(memory_file_name="current-project-status")

Example: Search for past filtering implementations

cipher_memory_search(query="image filtering feature implementation")

Example: Record your current task progress

mcp__serena__write_memory( memory_name="active-development-tasks", content="Implementing image filtering: FilterCriteria dataclass done." )

Example: Store a completed design decision

cipher_store_reasoning_memory( title="LoRAIro Image Filtering Design", content="Adopted dataclass for FilterCriteria for type safety." )

Frequently Asked Questions about mcp-memory-first-development

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

FAQPage Schema
How do I preserve development context when switching between tasks or team members?

Preserve development context by combining short-term project notes with long-term design knowledge. Use `mcp__serena__read_memory` to recall your last stopping point and `cipher_memory_search` to review relevant design patterns, then `mcp__serena__write_memory` to log progress. This dual-memory approach ensures seamless task handovers and eliminates redundant work.

What's the best way to document design decisions and avoid repeating past solutions?

Document design decisions systematically using `cipher_store_reasoning_memory` to capture design rationale and technical choices. Store patterns and lessons learned alongside short-term progress tracking. This builds a searchable archive you can query with `cipher_memory_search` before starting new features, preventing redundant implementation.

Can I use AI memory to track development progress across debugging sessions and refactors?

Yes. Record ongoing decisions, challenges, and next steps throughout pre-implementation, active development, and post-completion phases using short-term memory writes and long-term reasoning storage. Fast memory access (0.3–0.5s) with structured metadata enables quick retrieval across debugging sessions, refactors, and feature work.

How do I quickly recall past technical solutions and project status when picking up work after a break?

Use `mcp__serena__read_memory` to instantly recall your last stopping point, then `cipher_memory_search` to find relevant past solutions and design patterns. This eliminates context-switching overhead and leverages existing expertise stored from previous development cycles.

What knowledge management workflow integrates short-term notes with long-term design archives?

A dual-memory workflow combines Serena's rapid short-term project notes for immediate recall with Cipher's persistent, searchable design knowledge for patterns and decisions. Apply this across reconnaissance, active development, and knowledge capture phases to maintain comprehensive context with 0.3–0.5s access times.