Midtrans-Middleware/.bmad/bmb/reference/agents/expert-examples/journal-keeper/README.md

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# Expert Agent Reference: Personal Journal Keeper (Whisper)
This folder contains a complete reference implementation of a **BMAD Expert Agent** - an agent with persistent memory and domain-specific resources via a sidecar folder.
## Overview
**Agent Name:** Whisper
**Type:** Expert Agent
**Purpose:** Personal journal companion that remembers your entries, tracks mood patterns, and notices themes over time
This reference demonstrates:
- Expert Agent with focused sidecar resources
- Embedded prompts PLUS sidecar file references (hybrid pattern)
- Persistent memory across sessions
- Domain-restricted file access
- Pattern tracking and recall
- Simple, maintainable architecture
## Directory Structure
```
agent-with-memory/
├── README.md # This file
├── journal-keeper.agent.yaml # Main agent definition
└── journal-keeper-sidecar/ # Agent's private workspace
├── instructions.md # Core directives
├── memories.md # Persistent session memory
├── mood-patterns.md # Emotional tracking data
├── breakthroughs.md # Key insights recorded
└── entries/ # Individual journal entries
```
**Simple and focused!** Just 4 core files + a folder for entries.
## Key Architecture Patterns
### 1. Hybrid Command Pattern
Expert Agents can use BOTH:
- **Embedded prompts** via `action: "#prompt-id"` (like Simple Agents)
- **Sidecar file references** via direct paths
```yaml
menu:
# Embedded prompt (like Simple Agent)
- trigger: 'write'
action: '#guided-entry'
description: "Write today's journal entry"
# Direct sidecar file action
- trigger: 'insight'
action: 'Document this breakthrough in {agent-folder}/journal-keeper-sidecar/breakthroughs.md'
description: 'Record a meaningful insight'
```
This hybrid approach gives you the best of both worlds!
### 2. Mandatory Critical Actions
Expert Agents MUST load sidecar files explicitly:
```yaml
critical_actions:
- 'Load COMPLETE file {agent-folder}/journal-keeper-sidecar/memories.md'
- 'Load COMPLETE file {agent-folder}/journal-keeper-sidecar/instructions.md'
- 'ONLY read/write files in {agent-folder}/journal-keeper-sidecar/'
```
**Key points:**
- Files are loaded at startup
- Domain restriction is enforced
- Agent knows its boundaries
### 3. Persistent Memory Pattern
The `memories.md` file stores:
- User preferences and patterns
- Session notes and observations
- Recurring themes discovered
- Growth markers tracked
**Critically:** This is updated EVERY session, creating continuity.
### 4. Domain-Specific Tracking
Different files track different aspects:
- **memories.md** - Qualitative insights and observations
- **mood-patterns.md** - Quantitative emotional data
- **breakthroughs.md** - Significant moments
- **entries/** - The actual content (journal entries)
This separation makes data easy to reference and update.
### 5. Simple Sidecar Structure
Unlike modules with complex folder hierarchies, Expert Agent sidecars are flat and focused:
- Just the files the agent needs
- No nested workflows or templates
- Easy to understand and maintain
- All domain knowledge in one place
## Comparison: Simple vs Expert vs Module
| Feature | Simple Agent | Expert Agent | Module Agent |
| ------------- | -------------------- | -------------------------- | ---------------------- |
| Architecture | Single YAML | YAML + sidecar folder | YAML + module system |
| Memory | Session only | Persistent (sidecar files) | Config-driven |
| Prompts | Embedded only | Embedded + external files | Workflow references |
| Dependencies | None | Sidecar folder | Module workflows/tasks |
| Domain Access | None | Restricted to sidecar | Full module access |
| Complexity | Low | Medium | High |
| Use Case | Self-contained tools | Domain experts with memory | Full workflow systems |
## The Sweet Spot
Expert Agents are the middle ground:
- **More powerful** than Simple Agents (persistent memory, domain knowledge)
- **Simpler** than Module Agents (no workflow orchestration)
- **Focused** on specific domain expertise
- **Personal** to the user's needs
## When to Use Expert Agents
**Perfect for:**
- Personal assistants that need memory (journal keeper, diary, notes)
- Domain specialists with knowledge bases (specific project context)
- Agents that track patterns over time (mood, habits, progress)
- Privacy-focused tools with restricted access
- Tools that learn and adapt to individual users
**Key indicators:**
- Need to remember things between sessions
- Should only access specific folders/files
- Tracks data over time
- Adapts based on accumulated knowledge
## File Breakdown
### journal-keeper.agent.yaml
- Standard agent metadata and persona
- **Embedded prompts** for guided interactions
- **Menu commands** mixing both patterns
- **Critical actions** that load sidecar files
### instructions.md
- Core behavioral directives
- Journaling philosophy and approach
- File management protocols
- Tone and boundary guidelines
### memories.md
- User profile and preferences
- Recurring themes discovered
- Session notes and observations
- Accumulated knowledge about the user
### mood-patterns.md
- Quantitative tracking (mood scores, energy, etc.)
- Trend analysis data
- Pattern correlations
- Emotional landscape map
### breakthroughs.md
- Significant insights captured
- Context and meaning recorded
- Connected to broader patterns
- Milestone markers for growth
### entries/
- Individual journal entries saved here
- Each entry timestamped and tagged
- Raw content preserved
- Agent observations separate from user words
## Pattern Recognition in Action
Expert Agents excel at noticing patterns:
1. **Reference past sessions:** "Last week you mentioned feeling stuck..."
2. **Track quantitative data:** Mood scores over time
3. **Spot recurring themes:** Topics that keep surfacing
4. **Notice growth:** Changes in language, perspective, emotions
5. **Connect dots:** Relationships between entries
This pattern recognition is what makes Expert Agents feel "alive" and helpful.
## Usage Notes
### Starting Fresh
The sidecar files are templates. A new user would:
1. Start journaling with the agent
2. Agent fills in memories.md over time
3. Patterns emerge from accumulated data
4. Insights build from history
### Building Your Own Expert Agent
1. **Define the domain** - What specific area will this agent focus on?
2. **Choose sidecar files** - What data needs to be tracked/remembered?
3. **Mix command patterns** - Use embedded prompts + sidecar references
4. **Enforce boundaries** - Clearly state domain restrictions
5. **Design for accumulation** - How will memory grow over time?
### Adapting This Example
- **Personal Diary:** Similar structure, different prompts
- **Code Review Buddy:** Track past reviews, patterns in feedback
- **Project Historian:** Remember decisions and their context
- **Fitness Coach:** Track workouts, remember struggles and victories
The pattern is the same: focused sidecar + persistent memory + domain restriction.
## Key Takeaways
- **Expert Agents** bridge Simple and Module complexity
- **Sidecar folders** provide persistent, domain-specific memory
- **Hybrid commands** use both embedded prompts and file references
- **Pattern recognition** comes from accumulated data
- **Simple structure** keeps it maintainable
- **Domain restriction** ensures focused expertise
- **Memory is the superpower** - remembering makes the agent truly useful
---
_This reference shows how Expert Agents can be powerful memory-driven assistants while maintaining architectural simplicity._