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 co…
jrbobbyhansen-pixel
@jrbobbyhansen-pixel
What This Skill Does
Configures persistent memory search for Moltbot and Clawdbot agents by enabling memorySearch in config, creating MEMORY.md and daily log files, and setting up vector search with provider options like Voyage, OpenAI, or local embeddings.
Replaces agents forgetting context between sessions by giving them long-term recall of conversations, preferences, and project history.
When to Use It
- Enable memory search in clawdbot.json or moltbot.json config
- Create MEMORY.md with user facts, active projects, and preferences
- Set up daily log files in memory/logs/YYYY-MM-DD.md format
- Switch embedding provider from voyage to local when no API key is available
- Troubleshoot memory search not returning relevant results by lowering minScore
- Add agent instructions to AGENTS.md for memory recall behavior
Install
$ openclaw skills install @jrbobbyhansen-pixel/memory-setupMemory 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):
{
"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:
# 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 embeddingslocal— Local embeddings (no API needed)
Source Options
memory— MEMORY.md + memory/*.md filessessions— Past conversation transcriptsboth— Full context (recommended)
Daily Log Format
Create memory/logs/YYYY-MM-DD.md daily:
# 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:
## 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?
- Check
memorySearch.enabled: truein config - Verify MEMORY.md exists in workspace root
- Restart gateway:
clawdbot gateway restart
Results not relevant?
- Lower
minScoreto0.2for more results - Increase
maxResultsto30 - Check that memory files have meaningful content
Provider errors?
- Voyage: Set
VOYAGE_API_KEYin environment - OpenAI: Set
OPENAI_API_KEYin environment - Use
localprovider 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
{
"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. 🐘
Top skills in this category
self-improving agent
@pskoettCaptures and maintains learnings, errors, and corrections. Use when a command fails, the user corrects an assumption, a capability is missing, knowledge is outdated, or a better approach is found. Review relevant saved guidance before major tasks, reuse, and promotion; revalidate it according to wha
Self-Improving + Proactive Agent
@ivangdavilaSelf-reflection + Self-criticism + Self-learning + Self-organizing memory. Agent evaluates its own work, catches mistakes, and improves permanently. Use when...
ontology
@oswalpalashTyped knowledge graph for structured agent memory and composable skills. Use when creating/querying entities (Person, Project, Task, Event, Document), linkin...
Humanizer
@biostartechnologyRemove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
Obsidian
@steipeteWork with Obsidian vaults (plain Markdown notes) and automate via obsidian-cli.