Skill: gwsq/memory-setup-1-0-0 (version 1.0.0)

--- name: memory-setup description: 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. --- # 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. 🐘

path: _meta.json
content: ownerId: kn7536ghgpnachhadrck7hn5bs80206b
slug: memory-setup
version: 1.0.0
publishedAt: 1769568045678

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)