# Long Context

> Minimize startup context by loading MEMORY-LITE.md instead of full MEMORY.md. Use for session bootstrap optimization.

- Skill: `zhaog100/long-context` (Agent Skill, multi-file: 5 files)
- Install (CLI): `npx skillmds add zhaog100/long-context`
- Raw SKILL.md: https://api.skillmd.com/api/skills/zhaog100/long-context/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: zhaog100 (https://skillmd.com/u/zhaog100)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/zhaog100/long-context

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# Long Context v2.0.0

**创建者**: 思捷娅科技 (SJYKJ)/zhaog100

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MIT License

Copyright (c) 2026 思捷娅科技 (SJYKJ)

免费使用、修改和重新分发时，需注明出处。

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## Strategy: Startup Optimization

### File Hierarchy

| File | Size | Purpose | Loaded When |
|------|------|---------|-------------|
| MEMORY-LITE.md | ~2KB | Core identity, workflows, tracked PRs | **Every session startup** |
| MEMORY.md | ~10KB | Full history, detailed logs | Only when needed via memory_search |
| memory/YYYY-MM-DD.md | Variable | Daily raw notes | Only when searching specific dates |

### How It Works

1. **Startup**: Agent loads MEMORY-LITE.md (not full MEMORY.md)
2. **Deep recall**: Use `memory_search` to find specific information
3. **Detailed read**: Use `memory_get` to fetch specific lines from MEMORY.md

### Token Savings

- Before: MEMORY.md ~28KB → ~7000 tokens
- After: MEMORY-LITE.md ~2KB → ~500 tokens
- **Savings: ~6500 tokens per session startup**

## When to Use

- Session starts with large context files
- Need to recall historical events without loading full memory
- Want to reduce initial token consumption

## References

- Compaction patterns: `references/compaction.md`
- Memory search tips: `references/search-tips.md`