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Install in OpenClaw
/install nova-memory
Description
本地存储和语义检索工作空间记忆,支持实体管理、标签搜索、图谱可视化及自动反思,无外部依赖,安全可靠。
Usage Guidance
This skill mostly implements a local memory engine and does not exhibit network exfiltration, but there are mismatches you should address before installing: (1) The code requires scikit-learn (sklearn) though the metadata claims no external deps — install scikit-learn in an isolated virtualenv/conda environment before use. (2) memory_olap.py's docs mention DuckDB but it actually uses sqlite3 — verify behavior if you expect DuckDB. (3) The import error message suggests using '--break-system-packages' to install scikit-learn; avoid that flag in shared/system Python environments — prefer a virtualenv. (4) The skill writes JSON files under /workspace/memory/nova-memory/ (and auto_reflect can write to MEMORY.md); ensure you are comfortable with data being stored there and run the skill in a sandboxed workspace if the data is sensitive. (5) The provided source appears mostly benign, but part of memory_core.py was truncated in the bundle — inspect the full save/load implementation before trusting it with sensitive data. If you intend to use this skill, test it in an isolated environment and confirm scikit-learn installation and file I/O behavior; if you need stronger assurance, request the publisher/homepage or a signed release.
Capability Analysis
Type: OpenClaw Skill
Name: nova-memory
Version: 1.0.0
The nova-memory skill bundle provides a local semantic memory and entity management system using TF-IDF and SQLite for analysis. The implementation in memory_core.py and memory_olap.py is purely local, restricted to the /workspace/ directory, and lacks any network capabilities, obfuscation, or dangerous execution sinks like eval() or system calls. The code logic is transparent and aligns exactly with the functionality described in SKILL.md.
Capability Assessment
Purpose & Capability
The name/description claim a pure local Python implementation with no external dependencies, but src/memory_core.py imports scikit-learn (TfidfVectorizer, cosine_similarity). The SKILL metadata lists no required binaries or env vars and no install spec — yet the code requires an external Python package. Additionally, memory_olap.py's header and docstring reference DuckDB, but the implementation uses sqlite3 only. These mismatches are incoherent with the stated metadata and documentation.
Instruction Scope
SKILL.md and the CLI instruct the agent to read/write files under /workspace/memory/nova-memory/ and optionally write auto_reflect() outputs into MEMORY.md or memory/lessons.md — this is consistent with a local memory skill. The instructions do not direct reading of unrelated system files, network endpoints, or environment variables. Review of complete save/load code (partially truncated in provided file) is recommended to confirm there is no unexpected file access beyond the declared storage path.
Install Mechanism
There is no install specification (instruction-only), which is low risk, but the code has a hard dependency on scikit-learn. The package requirement is not declared in metadata; users will need to pip-install scikit-learn before using the skill. The ImportError message in memory_core.py suggests installing scikit-learn with the flag '--break-system-packages', which is unusual and risky advice (it can bypass some environment protections).
Credentials
The skill declares no required environment variables, credentials, or config paths, and the code does not reference external secrets or environment variables. That is proportionate for a local storage/analysis skill.
Persistence & Privilege
Flags show the skill is not 'always' included and can be invoked by users or autonomously (default). The skill reads/writes under /workspace/memory/nova-memory/, which is normal for a workspace-local memory tool and does not request elevated system-wide privileges.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install nova-memory - After installation, invoke the skill by name or use
/nova-memory - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
nova-memory 1.0.0 初始发布:
- 提供本地语义记忆存储与检索、实体管理、自动反思能力,纯 Python 实现,无外部依赖。
- 支持 TF-IDF + Cosine Similarity 本地语义检索、标签搜索、结构化实体图谱与索引。
- 集成 SQLite 本地 OLAP 模块,内置多维度分析(趋势、标签、实体、内容多样性)。
- 丰富 API & CLI 工具,便于开发者二次集成和终端快速操作。
- 数据本地安全持久化,每条存为 JSON,支持 save/load。
Metadata
Frequently Asked Questions
What is Nova Memory?
本地存储和语义检索工作空间记忆,支持实体管理、标签搜索、图谱可视化及自动反思,无外部依赖,安全可靠。 It is an AI Agent Skill for Claude Code / OpenClaw, with 71 downloads so far.
How do I install Nova Memory?
Run "/install nova-memory" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Nova Memory free?
Yes, Nova Memory is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Nova Memory support?
Nova Memory is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Nova Memory?
It is built and maintained by CatPluZ (@catplus-eric); the current version is v1.0.0.
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