# Memory Optimization

> Summarizing context, pruning history, and managing token budget efficiency.

- Skill: `majiayu000/memory-optimization-2` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds add majiayu000/memory-optimization-2`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/memory-optimization-2/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Finance & Business
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/memory-optimization-2

---


# memory-optimization Skill

This skill prevents "Context Overflow" and reduces API costs.

## 1. Summarization Strategies
- **Rolling Summary**: Keep the last 10 messages + a summary of everything before.
- **Entity Extraction**: Extract key facts ("User chose Redis", "App is on port 3000") and store in `semantic/`.

## 2. Context Pruning
- **Irrelevant Files**: Only keep file definitions in context if actively editing. Use `grep` for others.
- **Old Logs**: Truncate logs > 50 lines.

## 3. The "Forget" Protocol
- When a task is done:
  1.  **Summarize**: Write outcome to `AUDIT_LOG.md`.
  2.  **Clear**: Remove task-specific context from working memory.
  3.  **Retain**: Keep only global constraints and active file list.

## 4. Semantic Memory Integration
- Use **Qdrant** or **PGVector** (via MCP) to store embeddings of documentation.
- **Retrieval**: Retrieve only the Top-3 relevant chunks for the current query.