PARA Second Brain

使用 PARA（项目、区域、资源、档案）组织代理的知识 — 然后使其全部可搜索。符号链接技巧可以在整个知识库中进行完整的语义搜索，而不仅仅是 MEMORY.md。包括会话记录索引和内存刷新协议。你的特工终于拥有了真正的第二大脑。

## 概述（中文）

使用 PARA（项目、区域、资源、档案）组织代理的知识 — 然后使其全部可搜索。符号链接技巧可以在整个知识库中进行完整的语义搜索，而不仅仅是 MEMORY.md。包括会话记录索引和内存刷新协议。你的特工终于拥有了真正的第二大脑。

## 原文

# PARA Second Brain

Your agent's memory just got a massive upgrade. Full semantic search across your entire knowledge base — not just MEMORY.md.

## What's New in v2.0

**Before v2.0:** `memory_search` only found content in MEMORY.md and daily logs. Your entire `notes/` folder was invisible to search. You had to manually know where to look.

**After v2.0:** One symlink command makes your entire PARA knowledge base searchable. Ask about anything in your notes — it finds it. Plus session transcripts and memory flush protocol to prevent context loss.

| Before | After |
|--------|-------|
| Search only MEMORY.md + daily logs | Search EVERYTHING |
| "I don't have that information" | Finds it instantly |
| Context compaction = lost information | Flush protocol saves critical context |
| Conversations forgotten | Session transcripts indexed |

## What This Does

Creates a "second brain" structure that separates:
- **Raw capture** (daily logs) from **curated knowledge** (MEMORY.md)
- **Active work** (projects) from **ongoing responsibilities** (areas)
- **Reference material** (resources) from **completed work** (archive)

## How This Differs from Other Second Brain Skills

There's another popular [second-brain skill](https://clawdhub.com/christinetyip/second-brain) powered by Ensue. Both are great — they solve different problems:

| | **PARA Second Brain** (this skill) | **Ensue Second Brain** |
|---|---|---|
| **Storage** | Local files in your workspace | Cloud API (Ensue) |
| **Cost** | Free, self-hosted | Requires Ensue API key |
| **Best for** | Work context, agent continuity, project tracking | Evergreen knowledge base, semantic queries |
| **Search** | Clawdbot's `memory_search` | Ensue's vector search |
| **Structure** | PARA (Projects/Areas/Resources/Archive) | Namespaces (concepts/toolbox/patterns) |
| **Use case** | "What did we decide yesterday?" | "How does recursion work?" |

**Use this skill if:** You want file-based memory that works offline, costs nothing, and tracks ongoing work context.

**Use Ensue's skill if:** You want a cloud-hosted knowledge base optimized for semantic "what do I know about X" queries.

**Use both if:** You want PARA for work context + Ensue for evergreen knowledge. They complement each other.

## Quick Setup

### 1. Create Directory Structure

```
workspace/
├── MEMORY.md              # Curated long-term memory
├── memory/
│   └── YYYY-MM-DD.md      # Daily raw logs
└── notes/
    ├── projects/          # Active work with end dates
    ├── areas/             # Ongoing life responsibilities  
    ├── resources/         # Reference material
    │   └── templates/     # Content templates
    └── archive/           # Completed/inactive items
```

Run this to scaffold:
```bash
mkdir -p memory notes/projects notes/areas notes/resources/templates notes/archive
```

### 2. Make Notes Searchable (The Symlink Trick)

By default, `memory_search` only indexes `MEMORY.md` and `memory/*.md`. Your entire `notes/` folder is invisible to semantic search!

**Fix this with one command:**
```bash
ln -s /path/to/your/workspace/notes /path/to/your/workspace/memory/notes
```

Example:
```bash
ln -s /Users/yourname/clawd/notes /Users/yourname/clawd/memory/notes
```

**What this does:** Creates a symbolic link so `memory/notes/` points to your actual `notes/` folder. Now Clawdbot's memory_search sees all your PARA notes.

**Verify it worked:**
```bash
ls -la memory/notes  # Should show: memory/notes -> /path/to/notes
```

**Test the search:**
Ask your agent something that's in your notes but NOT in MEMORY.md. If it finds it, the symlink is working.

**Why this matters:**
| Before | After |
|--------|-------|
| Search only finds MEMORY.md + daily logs | Search finds ALL your notes |
| Must manually know where to look | Semantic search across everything |
| "I don't have that information" | Finds connections you forgot existed |

### 3. Enable Session Transcript Indexing

Make your past conversations searchable too. Add this to your Clawdbot config:

```json
"memorySearch": {
  "sources": ["memory", "sessions"],
  "query": {
    "minScore": 0.3,
    "maxResults": 20
  }
}
```

**What this does:** Indexes your conversation transcripts alongside your notes. Now when you ask "what did we discuss about X last week?" — it can actually find it.

### 4. Initialize MEMORY.md

Create `MEMORY.md` in workspace root - this is your curated long-term memory:

```markdown
# MEMORY.md — Long-Term Memory

## About [Human's Name]
- Role/occupation
- Key goals and motivations
- Communication preferences
- Important relationships

## Active Context
- Current focus areas
- Ongoing projects (summaries, not details)
- Deadlines or time-sensitive items

## Preferences & Patterns
- Tools and workflows they prefer
- Decision-making style
- Pet peeves and likes

## Lessons Learned
- What worked
- What didn't
- Principles discovered

## Key Dates
- Birthdays, anniversaries
- Recurring events
- Important milestones
```

### 5. Add to AGENTS.md

Add these instructions to your AGENTS.md:

```markdown
## Memory

You wake up fresh each session. These files are your continuity:
- **Daily notes:** `memory/YYYY-MM-DD.md` — raw logs of what happened
- **Long-term:** `MEMORY.md` — curated memories (like human long-term memory)
- **Topic notes:** `notes/` — organized by PARA structure (all searchable via memory_search)

### Writing Rules
- If it has future value, write it down NOW
- Don't rely on "mental notes" — they don't survive restarts
- Text > Brain 📝

### PARA Structure
- **Projects** (`notes/projects/`) — Active work with end dates
- **Areas** (`notes/areas/`) — Ongoing responsibilities (health, finances, relationships)
- **Resources** (`notes/resources/`) — Reference material, how-tos, research
- **Archive** (`notes/archive/`) — Completed or inactive items

### Memory Flush Protocol
Monitor your context usage with `session_status`. Before compaction wipes your memory, flush important context to files:

| Context % | Action |
|-----------|--------|
| < 50% | Normal operation |
| 50-70% | Write key points after substantial exchanges |
| 70-85% | Active flushing — write everything important NOW |
| > 85% | Emergency flush — full summary before next response |
| After compaction | Note what context may have been lost |

**The rule:** Act on thresholds, not vibes. If it's important, write it down NOW.
```

## Memory Flush Protocol (Critical!)

Your agent's context window is finite. When it fills up, older context gets compacted or lost. **Don't lose important information.**

### How to Monitor
Run `session_status` periodically. Look for:
```
📚 Context: 36k/200k (18%) · 🧹 Compactions: 0
```

### Threshold-Based Actions

| Context % | What to Do |
|-----------|------------|
| **< 50%** | Normal operation. Write decisions as they happen. |
| **50-70%** | Increased vigilance. Write key points after each substantial exchange. |
| **70-85%** | Active flushing. Write everything important to daily notes NOW. |
| **> 85%** | Emergency flush. Stop and write full context summary before responding. |
| **After compaction** | Immediately note what context may have been lost. Check continuity. |

### What to Flush
1. **Decisions made** — what was decided and why
2. **Action items** — who's doing what
3. **Open threads** — anything unfinished → `notes/areas/open-loops.md`
4. **Working changes** — if you discussed changes to files, make them NOW

### Memory Flush Checklist
Before a long session ends or context gets high:
- [ ] Key decisions documented?
- [ ] Action items captured?
- [ ] New learnings written to appropriate files?
- [ ] Open loops noted for follow-up?
- [ ] Could future-me continue this conversation from notes alone?

## Knowledge Quality

**The core question:** "Will future-me thank me for this?"

### What to Save
- Concepts you actually u