技能详情（站内镜像，无评论）
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v1.0.4
统计：⭐ 0 · 702 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal ：可疑 · OpenClaw ：良性
Package：alekhm/aister-vector-memory
安全扫描（ClawHub）
- VirusTotal ：可疑
- OpenClaw ：良性
OpenClaw 评估
The skill implements a local vector-memory (Postgres + pgvector + a local embedding service) and the code, docs, and runtime instructions are consistent with that purpose — but there are a few housekeeping inconsistencies and things to watch (metadata omission of the required DB password, model download from HuggingFace, and optional autostart that edits your shell).
目的
The files and SKILL.md consistently describe a local vector memory using PostgreSQL + pgvector and a local embedding service (intfloat/e5-large-v2). Requiring a DB password and a local embedding service is appropriate for this purpose. However the registry metadata claims no required environment variables while SKILL.md and the scripts require VECTOR_MEMORY_DB_PASSWORD — that's an inconsistency in the package metadata (likely an omission) and …
说明范围
Runtime instructions and scripts only read expected memory files (MEMORY.md, IDENTITY.md, USER.md), call the local embedding service, and operate on the specified database tables. The docs explicitly warn about not putting secrets in memory files. Two items to note: (1) first run downloads a ~1.3GB model from HuggingFace (network access required); (2) INSTALL.md proposes optional autostart by appending a nohup/start snippet to the user's shell…
安装机制
This is an instruction-only skill (no install spec) with included Python scripts. The only external download is the embedding model from HuggingFace (expected for embedding workflows). No downloads from obscure or shortener URLs or arbitrary remote code execution are present in the skill itself. The usual supply-chain note applies: large model weights are fetched from an external provider and should be considered a supply-chain risk if that so…
证书
The only secret the skill requires at runtime is the PostgreSQL password (VECTOR_MEMORY_DB_PASSWORD), which is proportional to its purpose. The docs also note the need for PostgreSQL superuser/root during installation to create extensions — that is typical for installing pgvector. The earlier metadata omission of required env vars is the main mismatch to fix.
持久
The skill does not request always:true and does not declare elevated platform privileges. It does recommend (optionally) adding an autostart snippet to the user's shell profile and running a background Flask service; those are common for a long-running local service but are changes to user dotfiles. The docs recommend Docker for isolation, which mitigates persistence/privilege concerns.
综合结论
This skill appears to be what it says: a local vector-memory using PostgreSQL + pgvector and a local embedding service. Before installing: (1) correct/confirm metadata — set VECTOR_MEMORY_DB_PASSWORD (the registry metadata omitted this required env var); (2) review the three included Python scripts yourself (embedding_service.py, memory_reindex.py, memory_search.py); (3) run in a container/VM if you want isolation (the README recommends Docker…
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Aister vector-memory」。简介：Provides semantic vector search over Aister's memory using PostgreSQL and e5-la…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/alekhm/aister-vector-memory/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
暂无本地缓存内容，可在后台执行详情同步。