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layered-context

myths-labs/muse/skills/core/layered-context/SKILL.md

L0/L1/L2 three-layer context loading protocol — reduces token consumption during /resume boot

Skill35 starsChanged 6 months ago

What's in it

  1. Layered Context Loading Protocol
  2. Why
  3. Three Layers
  4. L0 Format
  5. L0 Content Rules
  6. L0 Examples
  7. Boot Sequence with Layered Loading
  8. Decision Tree: When to Upgrade
  9. Maintaining L0
  10. Who Updates L0
  11. L0 Staleness Detection
---
name: layered-context
description: L0/L1/L2 three-layer context loading protocol — reduces token consumption during /resume boot
---

# Layered Context Loading Protocol

> Inspired by OpenViking (ByteDance) L0/L1/L2 architecture.
> Adapted for MUSE's on-demand Markdown context loading.

## Why

Full-loading all `.muse/*.md` files during `/resume` wastes tokens when the Agent only needs one role's context. The layered approach loads minimum context first, then deepens on demand.

## Three Layers

| Layer | Token Budget | Content | When to Load |
|:-----:|:-----------:|---------|-------------|
| **L0** | ~100 tokens | One-line HTML comment at top of each `.muse/*.md` | **Always** — scan ALL role files |
| **L1** | ~2K tokens | Full role file content | **On demand** — only the CURRENT role's file |
| **L2** | Unbounded | `memory/*.md` + code files + docs | **On demand** — grep search when needed |

## L0 Format

Every `.muse/*.md` file MUST have an L0 comment as the **first line**:

```html
<!-- L0: v2.10.1 | P0=竞品技术吸收, P1/P2全清, QA PASS, S036已接收 -->
```

### L0 Content Rules

1. **Max 120 characters** (excluding `<!-- L0: ` and ` -->`)
2. **Must include**: current version + top priority + blocking issues
3. **Pipe-separated** sections: `version | priorities | status`
4. **Updated every /bye** — when the role file is synced

### L0 Examples

```html
<!-- L0: v2.10.1 | P0=竞品技术吸收(mem0/OpenViking), P1全清, QA 10/10 PASS -->
<!-- L0: 9/9渠道已发, Show HN暂缓, S040梗图排期中, Stars=2 -->
<!-- L0: 最近QA全PASS(10/10 v2.3), 无待修FAIL, QA清洁状态 -->
```

## Boot Sequence with Layered Loading

```
/resume [role]
  │
  ├─① Read CLAUDE.md + MEMORIES.md (constitutional layer, always)
  │
  ├─② Scan ALL .muse/*.md L0 lines (grep "<!-- L0:" .muse/*.md)
  │   → Get one-liner status of every role in ~400 tokens total
  │
  ├─③ Deep-read CURRENT role's .muse/*.md (L1, full file)
  │   → Only the file matching /resume [role]
  │
  ├─④ Scan memory/ for unfinished items (L2, on demand)
  │   → grep 🔲 and [ ] in recent memory files
  │
  └─⑤ grep strategy.md for 🟡 directives (L2, on demand)
      → Only if non-strategy role
```

## Decision Tree: When to Upgrade

```
Agent receives a question/task
  │
  ├─ Can answer from L0? → Answer immediately
  │   (e.g., "What version is MUSE?" → L0 has it)
  │
  ├─ Need role details? → Load L1 (full role file)
  │   (e.g., "What's the P0 task?" → need build.md details)
  │
  └─ Need historical context? → Load L2 (memory/grep)
      (e.g., "What did we decide about X last week?" → grep memory/)
```

## Maintaining L0

### Who Updates L0

The **`/bye` workflow** updates L0 as part of Step 3.5 (role file sync):
1. After syncing the role file content
2. Rewrite the L0 comment to reflect current state
3. Keep within 120 char limit

### L0 Staleness Detection

If the L0 comment's version doesn't match the latest tag, the `/resume` boot should flag it:
```
⚠️ L0 stale: build.md says v2.10.1 but latest tag is v2.11.0
```

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