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Smara Memory

Persistent memory for AI agents — store, search, and recall user context via the Smara Memory API
为 AI 代理提供持久记忆 — 通过 Smara Memory API 存储、搜索和检索用户上下文
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未分类 clawhub v1.0.0 1 版本 100000 Key: 需要
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概述

Smara Memory Skill

Gives your agent persistent memory across conversations. Store facts about users, search by meaning, and retrieve full context — powered by Smara's Ebbinghaus decay scoring.

When to use

  • When the agent learns something about a user that should persist (preferences, facts, context)
  • When the agent needs to recall what it knows about a user
  • When the agent should check if it already knows something before asking again
  • After meaningful conversations to extract and store key facts

Setup

  1. Get a free API key at https://smara.io
  2. Set SMARA_API_KEY in your environment

Actions

Store a memory

curl -X POST https://api.smara.io/v1/memories \
  -H "Authorization: Bearer $SMARA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "user_id": "user_id_here",
    "fact": "User prefers dark mode and uses vim keybindings",
    "importance": 0.7
  }'

Search memories

curl "https://api.smara.io/v1/memories/search?user_id=user_id_here&query=editor+preferences&limit=5" \
  -H "Authorization: Bearer $SMARA_API_KEY"

Get full user context

curl "https://api.smara.io/v1/users/user_id_here/context" \
  -H "Authorization: Bearer $SMARA_API_KEY"

Delete a memory

curl -X DELETE "https://api.smara.io/v1/memories/MEMORY_ID" \
  -H "Authorization: Bearer $SMARA_API_KEY"

Instructions for the agent

  1. After conversations: Extract key facts (preferences, decisions, context) and store them as memories with relevant tags
  2. Before responding: Search for relevant memories to personalize responses
  3. Contradiction handling: Smara automatically handles contradictions — if a user changes a preference, just store the new one and the old one is soft-deleted
  4. Duplicate handling: Smara skips duplicates automatically — safe to store the same fact multiple times
  5. Decay scoring: Memories naturally lose weight over time. Recent, frequently-accessed memories rank higher. This is automatic.

Example workflow

User: "I switched to Neovim last week"

Agent thinks:
1. Search memories for "editor preferences" → finds "Uses vim keybindings"
2. Store new memory: "Switched to Neovim (from vim)" with tags ["preferences", "editor"]
3. Smara auto-detects contradiction with old vim memory → soft-deletes it
4. Respond acknowledging the switch

API Reference

Full docs: https://api.smara.io/docs/

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-05-07 10:32 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
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腾讯云安全 (Sanbu)

安全,无风险
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