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Your agent can:\n- Remember user preferences across sessions\n- Store conversation history beyond context limits\n- Share memory with other agents\n- Never hallucinate forgotten details again\n\n## Installation\n\n```bash\nnpx clawhub install sq-memory\n```\n\nOr manually:\n```bash\ngit clone https://github.com/wbic16/openclaw-sq-skill.git ~/.openclaw/skills/sq-memory\n```\n\n## Configuration\n\nAdd to your agent's `.openclaw/config.yaml`:\n\n```yaml\nskills:\n  sq-memory:\n    enabled: true\n    endpoint: http://localhost:1337\n    username: your-username\n    password: your-api-key\n    namespace: agent-name  # Isolates this agent's memory\n```\n\n## Usage\n\nYour agent automatically gets new memory tools:\n\n### remember(key, value)\nStore something for later:\n```javascript\nremember(\"user/name\", \"Alice\")\nremember(\"user/preferences/theme\", \"dark\")\nremember(\"conversation/2026-02-11/summary\", \"Discussed phext storage...\")\n```\n\n### recall(key)\nRetrieve stored memory:\n```javascript\nconst name = recall(\"user/name\")  // \"Alice\"\nconst theme = recall(\"user/preferences/theme\")  // \"dark\"\n```\n\n### forget(key)\nDelete memory:\n```javascript\nforget(\"conversation/2026-02-11/summary\")\n```\n\n### list_memories(prefix)\nList all memories under a coordinate:\n```javascript\nconst prefs = list_memories(\"user/preferences/\")\n// Returns: [\"user/preferences/theme\", \"user/preferences/language\", ...]\n```\n\n## Coordinate Structure\n\nMemories are stored at 11D coordinates. The skill uses this convention:\n\n```\nnamespace.1.1 / category.subcategory.item / 1.1.1\n```\n\nExample:\n- Agent namespace: `my-assistant`\n- User preference for theme: `my-assistant.1.1/user.preferences.theme/1.1.1`\n\nThis means:\n- Each agent has isolated memory (namespace collision impossible)\n- Memories are hierarchically organized\n- You can share coordinates between agents if needed\n\n## Example: User Preference Agent\n\n```javascript\n// In your agent's system prompt or skill code:\n\nasync function getUserTheme() {\n  const theme = recall(\"user/preferences/theme\")\n  return theme || \"light\"  // Default to light if not set\n}\n\nasync function setUserTheme(newTheme) {\n  remember(\"user/preferences/theme\", newTheme)\n  return `Theme set to ${newTheme}`\n}\n\n// Agent conversation:\nUser: \"I prefer dark mode\"\nAgent: *calls setUserTheme(\"dark\")*\nAgent: \"Got it! I've set your theme to dark mode.\"\n\n// Next session (days later):\nUser: \"What's my preferred theme?\"\nAgent: *calls getUserTheme()*\nAgent: \"You prefer dark mode.\"\n```\n\n## Example: Conversation History\n\n```javascript\n// Store conversation summaries beyond context window:\n\nasync function summarizeAndStore(conversationId, summary) {\n  const date = new Date().toISOString().split('T')[0]\n  const key = `conversations/${date}/${conversationId}/summary`\n  remember(key, summary)\n}\n\nasync function recallConversation(conversationId) {\n  const memories = list_memories(`conversations/`)\n  return memories\n    .filter(m => m.includes(conversationId))\n    .map(key => recall(key))\n}\n\n// Usage:\nsummarizeAndStore(\"conv-123\", \"User asked about phext storage, explained 11D coordinates\")\n\n// Later:\nconst history = recallConversation(\"conv-123\")\n// Agent can recall what was discussed even after context window cleared\n```\n\n## Advanced: Multi-Agent Coordination\n\nMultiple agents can share memory at agreed coordinates:\n\n**Agent A (writes):**\n```javascript\nremember(\"shared/tasks/pending/task-42\", \"Review pull request #123\")\n```\n\n**Agent B (reads):**\n```javascript\nconst task = recall(\"shared/tasks/pending/task-42\")\n// Sees: \"Review pull request #123\"\n```\n\nThis enables true multi-agent workflows.\n\n## API Reference\n\nAll functions are available in the `sq` namespace:\n\n### sq.remember(coordinate, text)\n- **coordinate**: String in format `a.b.c/d.e.f/g.h.i` or shorthand `category/item`\n- **text**: String to store (max 1MB per coordinate)\n- **Returns**: `{success: true, coordinate: \"full.coordinate.path\"}`\n\n### sq.recall(coordinate)\n- **coordinate**: String (exact match)\n- **Returns**: String (stored text) or `null` if not found\n\n### sq.forget(coordinate)\n- **coordinate**: String (exact match)\n- **Returns**: `{success: true}` or `{success: false, error: \"...\"}`\n\n### sq.list_memories(prefix)\n- **prefix**: String (e.g., `\"user/\"` matches all user memories)\n- **Returns**: Array of coordinate strings\n\n### sq.update(coordinate, text)\n- Alias for `remember()` (overwrites existing)\n\n## Rate Limits\n\n- **Free tier**: 1,000 API calls/day, 100MB storage\n- **SQ Cloud ($50/mo)**: 10,000 API calls/day, 1TB storage\n- **Enterprise**: Custom limits\n\n## Troubleshooting\n\n**\"Connection refused\" error:**\n- Check your `endpoint` in config (should be `https://sq.mirrorborn.us`)\n- Verify credentials are correct\n\n**\"Quota exceeded\" error:**\n- You've hit rate limits\n- Upgrade to SQ Cloud or wait for daily reset\n\n**Memory not persisting:**\n- Check namespace isolation (each agent needs unique namespace)\n- Verify coordinate format is valid\n\n## Why SQ?\n\n**Open source & MIT licensed:**\n- Run it yourself for free\n- Modify it to fit your needs\n- No vendor lock-in\n- Transparent codebase\n\n**Not a vector database:**\n- Agents can *read* stored text (not just search embeddings)\n- Structured by coordinates (not similarity)\n- Deterministic retrieval (no relevance ranking guesses)\n\n**Not Redis:**\n- Persistent (survives restarts)\n- 11D addressing (not flat key-value)\n- Immutable history (WAL for time-travel)\n\n**Built for agents:**\n- Coordinate system matches agent thinking (hierarchical)\n- No schema overhead\n- Scales from KB to TB\n\n## Get SQ\n\n**Self-Host (Free):**\n1. 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