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在 OpenClaw 中安装
/install agent-memory-persistence
功能描述
Provide long-term memory persistence for AI agents with SQLite-backed storage, structured metadata, vector embeddings, semantic retrieval, lifecycle manageme...
使用说明 (SKILL.md)
Agent Memory Persistence
Use this skill when an agent needs durable memory storage across sessions.
What it provides
- SQLite-backed persistence for text, metadata, and embedding vectors
- CRUD operations for memory items
- Semantic retrieval with cosine-similarity vector search
- Memory lifecycle operations including expiration cleanup
- Filters by user, session, type, and time window
Project structure
src/MemoryStore.ts: low-level SQLite storage enginesrc/VectorIndex.ts: vector similarity search over stored embeddingssrc/MemoryManager.ts: high-level API used by agentssrc/types.ts: shared TypeScript contracts
Usage pattern
- Create a
MemoryManagerwith a SQLite path. - Write memories with
content, optionalmetadata, and optionalembedding. - Query memories by session/user or use
searchByVector()for semantic lookup. - Periodically call
cleanupExpired()to delete stale memories.
Notes
- Embeddings are stored as JSON arrays in SQLite.
- Vector search is implemented in TypeScript using cosine similarity, which keeps deployment simple and avoids SQLite extensions.
- If memory volume grows substantially, replace
VectorIndexwith an ANN index or SQLite vector extension while preserving theMemoryManagerAPI.
安全使用建议
This package appears to do what it says: a local SQLite-backed memory store with vector search implemented in TypeScript. Before installing, confirm you have Node.js and a C toolchain available (better-sqlite3 is a native module and may compile during npm install). Because the registry entry doesn't declare Node/npm or filesystem write access, verify the runtime environment and run it in a sandbox if you have sensitive data. Review or pin the dependency versions, and consider encrypting or limiting sensitive data stored in the DB since memories are stored locally in plain JSON by default. If you need networked persistence or large-scale vector search, plan for replacing the in-memory TS vector search with an ANN index or a proper vector-enabled DB.
功能分析
Type: OpenClaw Skill
Name: agent-memory-persistence
Version: 0.1.0
The skill bundle provides a legitimate and well-implemented SQLite-backed memory persistence layer for AI agents. It uses prepared statements in `src/MemoryStore.ts` to prevent SQL injection and implements standard cosine similarity for vector search in `src/VectorIndex.ts` without any suspicious external dependencies, network activity, or prompt injection attempts.
能力评估
Purpose & Capability
The name/description, SKILL.md, and source files all describe a local SQLite-backed memory manager with embeddings and semantic search — this is coherent. However, the registry metadata declares no required binaries or environment, while the package includes Node TypeScript source and a package.json that depends on better-sqlite3. In practice this requires a Node.js runtime and dependency installation (and better-sqlite3 is a native module that may need a C toolchain). The skill also needs filesystem access for the SQLite DB path. These runtime requirements are not declared in the registry and should be noted.
Instruction Scope
SKILL.md stays within scope: create a MemoryManager with a SQLite path, CRUD, vector search, and cleanup. The runtime instructions and code do not read unrelated system files, access environment variables, or call external network endpoints. Tests use temporary directories only. No instructions request sending data to third parties.
Install Mechanism
The registry lists no install spec, but the package includes source files and package.json with a dependency on better-sqlite3. There is no URL download or remote script; installation is via npm (implicit). That npm dependency may invoke native compilation (better-sqlite3) which requires tooling and may fail on constrained environments. Absence of an explicit install spec or declared required binaries (node/npm) is an incoherence to be aware of, but not malicious.
Credentials
The skill does not request any environment variables, secrets, or unrelated credentials. The code likewise does not read environment variables or attempt to access credentials. Its data access is limited to the SQLite DB path you provide.
Persistence & Privilege
The skill does not request permanent/always-on inclusion and will not modify other skills or global agent settings. It persists data only to the SQLite database you instantiate (default :memory: unless you pass a filesystem path). Autonomous invocation is permitted by default (normal), but that is not combined with other concerning privileges here.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install agent-memory-persistence - 安装完成后，直接呼叫该 Skill 的名称或使用
/agent-memory-persistence触发 - 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
v0.1.0
Initial release
元数据
常见问题
Agent Memory Persistence 是什么？
Provide long-term memory persistence for AI agents with SQLite-backed storage, structured metadata, vector embeddings, semantic retrieval, lifecycle manageme... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 500 次。
如何安装 Agent Memory Persistence？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install agent-memory-persistence」即可一键安装，无需额外配置。
Agent Memory Persistence 是免费的吗？
是的，Agent Memory Persistence 完全免费（开源免费），可自由下载、安装和使用。
Agent Memory Persistence 支持哪些平台？
Agent Memory Persistence 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 Agent Memory Persistence？
由 imgolye（@imgolye）开发并维护，当前版本 v0.1.0。
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