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
memory-manager
Local memory management for agents. Compression detection, auto-snapshots, and semantic search. Use when agents need to detect compression risk before memory loss, save context snapshots, search historical memories, or track memory usage patterns. Never lose context again.
memory-hygiene
Audit, clean, and optimize Clawdbot's vector memory (LanceDB). Use when memory is bloated with junk, token usage is high from irrelevant auto-recalls, or setting up memory maintenance automation.
expo-tailwind-setup
Set up Tailwind CSS v4 in Expo with react-native-css and NativeWind v5 for universal styling
elite-longterm-memory
Ultimate AI agent memory system for Cursor, Claude, ChatGPT & Copilot. WAL protocol + vector search + git-notes + cloud backup. Never lose context again. Vibe-coding ready.
ab-test-setup
When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "conversion experiment," "statistical significance," or "test this." For tracking implementation, see analytics-tracking.
setup
Set up a new autoresearch experiment interactively. Collects domain, target file, eval command, metric, direction, and evaluator.
auto-memory-pro
Curate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity.
AgentMemory Skill
Persistent memory system for AI agents. Remember facts, learn from experience, and track entities across sessions.
youtube-watcher
Fetch and read transcripts from YouTube videos. Use when you need to summarize a video, answer questions about its content, or extract information from it.
youtube-transcript
Fetch and summarize YouTube video transcripts. Use when asked to summarize, transcribe, or extract content from YouTube videos. Handles transcript fetching via residential IP proxy to bypass YouTube's cloud IP blocks.
youtube-auto-captions - YouTube 自动字幕
## 描述
youtube
YouTube Data API integration with managed OAuth. Search videos, manage playlists, access channel data, and interact with comments. Use this skill when users want to interact with YouTube. For other third party apps, use the api-gateway skill (https://clawhub.ai/byungkyu/api-gateway).