memory-setup
Enable and configure Moltbot/Clawdbot memory search for persistent context. Use when setting up memory, fixing "goldfish brain," or helping users configure memorySearch in their config. Covers MEMORY.md, daily logs, and vector search setup.
Best use case
memory-setup is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Enable and configure Moltbot/Clawdbot memory search for persistent context. Use when setting up memory, fixing "goldfish brain," or helping users configure memorySearch in their config. Covers MEMORY.md, daily logs, and vector search setup.
Teams using memory-setup should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/memory-setup/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How memory-setup Compares
| Feature / Agent | memory-setup | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Enable and configure Moltbot/Clawdbot memory search for persistent context. Use when setting up memory, fixing "goldfish brain," or helping users configure memorySearch in their config. Covers MEMORY.md, daily logs, and vector search setup.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Memory Setup Skill
Transform your agent from goldfish to elephant. This skill helps configure persistent memory for Moltbot/Clawdbot.
## Quick Setup
### 1. Enable Memory Search in Config
Add to `~/.clawdbot/clawdbot.json` (or `moltbot.json`):
```json
{
"memorySearch": {
"enabled": true,
"provider": "voyage",
"sources": ["memory", "sessions"],
"indexMode": "hot",
"minScore": 0.3,
"maxResults": 20
}
}
```
### 2. Create Memory Structure
In your workspace, create:
```
workspace/
├── MEMORY.md # Long-term curated memory
└── memory/
├── logs/ # Daily logs (YYYY-MM-DD.md)
├── projects/ # Project-specific context
├── groups/ # Group chat context
└── system/ # Preferences, setup notes
```
### 3. Initialize MEMORY.md
Create `MEMORY.md` in workspace root:
```markdown
# MEMORY.md — Long-Term Memory
## About [User Name]
- Key facts, preferences, context
## Active Projects
- Project summaries and status
## Decisions & Lessons
- Important choices made
- Lessons learned
## Preferences
- Communication style
- Tools and workflows
```
## Config Options Explained
| Setting | Purpose | Recommended |
|---------|---------|-------------|
| `enabled` | Turn on memory search | `true` |
| `provider` | Embedding provider | `"voyage"` |
| `sources` | What to index | `["memory", "sessions"]` |
| `indexMode` | When to index | `"hot"` (real-time) |
| `minScore` | Relevance threshold | `0.3` (lower = more results) |
| `maxResults` | Max snippets returned | `20` |
### Provider Options
- `voyage` — Voyage AI embeddings (recommended)
- `openai` — OpenAI embeddings
- `local` — Local embeddings (no API needed)
### Source Options
- `memory` — MEMORY.md + memory/*.md files
- `sessions` — Past conversation transcripts
- `both` — Full context (recommended)
## Daily Log Format
Create `memory/logs/YYYY-MM-DD.md` daily:
```markdown
# YYYY-MM-DD — Daily Log
## [Time] — [Event/Task]
- What happened
- Decisions made
- Follow-ups needed
## [Time] — [Another Event]
- Details
```
## Agent Instructions (AGENTS.md)
Add to your AGENTS.md for agent behavior:
```markdown
## Memory Recall
Before answering questions about prior work, decisions, dates, people, preferences, or todos:
1. Run memory_search with relevant query
2. Use memory_get to pull specific lines if needed
3. If low confidence after search, say you checked
```
## Troubleshooting
### Memory search not working?
1. Check `memorySearch.enabled: true` in config
2. Verify MEMORY.md exists in workspace root
3. Restart gateway: `clawdbot gateway restart`
### Results not relevant?
- Lower `minScore` to `0.2` for more results
- Increase `maxResults` to `30`
- Check that memory files have meaningful content
### Provider errors?
- Voyage: Set `VOYAGE_API_KEY` in environment
- OpenAI: Set `OPENAI_API_KEY` in environment
- Use `local` provider if no API keys available
## Verification
Test memory is working:
```
User: "What do you remember about [past topic]?"
Agent: [Should search memory and return relevant context]
```
If agent has no memory, config isn't applied. Restart gateway.
## Full Config Example
```json
{
"memorySearch": {
"enabled": true,
"provider": "voyage",
"sources": ["memory", "sessions"],
"indexMode": "hot",
"minScore": 0.3,
"maxResults": 20
},
"workspace": "/path/to/your/workspace"
}
```
## Why This Matters
Without memory:
- Agent forgets everything between sessions
- Repeats questions, loses context
- No continuity on projects
With memory:
- Recalls past conversations
- Knows your preferences
- Tracks project history
- Builds relationship over time
Goldfish → Elephant. 🐘Related Skills
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