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Smara Memory

作者 parallelromb · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install smara-memory
功能描述
Persistent memory for AI agents — store, search, and recall user context via the Smara Memory API
使用说明 (SKILL.md)

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/

安全使用建议
This skill is coherent for storing and recalling conversation memory, but before installing: (1) Verify Smara (https://smara.io) and read their privacy/retention/security docs; (2) Use a scoped API key and rotate/revoke it if needed; (3) Avoid automatically storing highly sensitive PII (SSNs, full credit card numbers, medical records); (4) Decide whether the agent may auto-store facts or should require user consent for persistent storage; (5) Monitor API usage and logs for unexpected activity. If you need stronger guarantees, ask the provider about encryption-at-rest, data deletion policies, and whether you can redact or hash identifiers before sending.
能力评估
Purpose & Capability
Name/description, examples, and requested env var (SMARA_API_KEY) all match a memory/storage service. No unrelated credentials, binaries, or config paths are requested.
Instruction Scope
SKILL.md only instructs the agent to call Smara API endpoints (store, search, get context, delete) and to extract facts from conversations. This is within scope, but the instructions imply storing user facts which can include sensitive personal data—understand privacy/retention implications before enabling automatic storage.
Install Mechanism
Instruction-only skill with no install spec or code files; nothing will be written to disk by an installer. This is the lowest-risk install model.
Credentials
Only a single API key (SMARA_API_KEY) is required and is the declared primary credential. This is proportionate to a remote memory service.
Persistence & Privilege
always is false and the skill is user-invocable; model invocation is allowed (default). Autonomous use plus persistent memory is expected for this skill but increases the impact if the external service or key is compromised—consider limiting scope and monitoring usage.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install smara-memory
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /smara-memory 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release — store, search, context, delete memories via Smara API. Ebbinghaus decay scoring, contradiction detection, zero infrastructure.
元数据
Slug smara-memory
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Smara Memory 是什么?

Persistent memory for AI agents — store, search, and recall user context via the Smara Memory API. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 104 次。

如何安装 Smara Memory?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install smara-memory」即可一键安装,无需额外配置。

Smara Memory 是免费的吗?

是的,Smara Memory 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Smara Memory 支持哪些平台?

Smara Memory 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Smara Memory?

由 parallelromb(@parallelromb)开发并维护,当前版本 v1.0.0。

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