← Back to Skills Marketplace
54
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install z1-memory-palace
Description
File-based long-term AI memory system with BGE-M3 vector search, metadata filtering, compound scoring, graph-based neighbor expansion, and automated memory m...
Usage Guidance
Don't run these scripts unchanged. Key risks and actions to consider:
- The code hardcodes ROOT = /Users/zhouyi0415126.com/ai_matrix/vault/01_core; it will not operate on a palace/ you create in the current directory. Before running, either change ROOT to a safe test directory or run inside a disposable copy of your repository.
- The scripts perform filesystem writes (rename backup of manifest, overwrite index files, write graph JSON). Backup your data first and inspect the manifest/index files before running write operations.
- SKILL.md suggests pip install FlagEmbedding (third-party package). Audit that package (source, PyPI page) before installing and consider installing into an isolated virtualenv.
- There are path mismatches (scripts call scripts/watchdog/*.py but files are in scripts/). Expect runtime failures and review/normalize paths.
- The tool will encode text with a BGEM3FlagModel which may contact remote model services; confirm network behavior and any credentials required by the FlagEmbedding library.
- If you want to use this skill, adapt ROOT and script paths to a sandbox/test directory, run dry-runs, and only enable any scheduled/automated runs after verifying effects. If uncertain, ask the author for a repackaged version that uses relative paths or accepts a configurable root path and documents expected side effects.
Capability Analysis
Type: OpenClaw Skill
Name: z1-memory-palace
Version: 3.0.0
The bundle implements a functional file-based RAG (Retrieval-Augmented Generation) system, but contains high-risk patterns including hardcoded absolute paths and shell execution. Multiple scripts (build_index_bge.py, query_bge.py, cold_zone_blinding_patch.py) use a hardcoded path (/Users/zhouyi0415126.com/ai_matrix/vault/01_core), which is a significant security flaw for shared code. Additionally, auto_maintain.sh and build_index_bge.py execute shell commands (git diff) and imply persistence via LaunchAgents. While no clear evidence of data exfiltration or intentional malice was found, the lack of path generalization and the use of system-level scripts for local file manipulation represent a high risk to the host environment.
Capability Assessment
Purpose & Capability
The skill claims a file-based, zero-infrastructure memory palace you can initialize in the current working directory, but the Python and shell scripts are written to operate on a hardcoded absolute ROOT (/Users/zhouyi0415126.com/ai_matrix/vault/01_core). That means running the provided scripts will not act on the local 'palace/' you create unless you edit the code. This mismatch is unexpected for the claimed purpose and suggests poor packaging or that the code was copied from a single developer's machine.
Instruction Scope
SKILL.md tells the agent/user to create palace/ in the current directory and run pip install FlagEmbedding and the build/query scripts. The code, however, reads/writes manifests, index and graph files under the absolute ROOT path and performs file operations (renaming manifest to a .backup, writing indexes, writing graph_neighbors). auto_maintain.sh also cd's into the hardcoded path and calls scripts under scripts/watchdog/, but the included files are in scripts/ (no watchog subdir). These instructions will either fail or operate on unexpected files; they also perform writes/renames on the user's filesystem (expected for an indexer but important to be explicit).
Install Mechanism
There is no formal install spec; SKILL.md suggests pip install FlagEmbedding. That is a moderate-risk dependency (unknown third-party package) but not inherently malicious. Because this is instruction-only with code files, nothing is automatically written to disk by the registry, but following the instructions will install a third-party Python package and run local scripts that modify files.
Credentials
The skill does not request environment variables or credentials. However, it expects filesystem access to a specific absolute path and will read and write files there (manifests, index, backups, graph). That filesystem access is proportional for a local memory manager, but the hardcoded path is disproportionate to the 'zero-infrastructure' claim and increases risk of accidental modification of unrelated user data if the path is adapted incorrectly.
Persistence & Privilege
The skill is not marked 'always' and does not itself install persistent agents. It contains an auto_maintain.sh that is intended to be run by a LaunchAgent daily (comment only). If a user or integrator wires this into a scheduler, it will perform recurring writes and rebuilds on the hardcoded vault. That persistent operation would increase blast radius, so treat automated scheduling cautiously.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install z1-memory-palace - After installation, invoke the skill by name or use
/z1-memory-palace - Provide required inputs per the skill's parameter spec and get structured output
Version History
v3.0.0
Compound scoring (semantic 50% + recency 25% + importance 25%), metadata pre-filtering (--type/--priority), BGE-m3 index enhanced with mtime field, memory metabolism protocol, chamber accumulated knowledge system. Zero Docker, zero external services.
Metadata
Frequently Asked Questions
What is Z1 Memory Palace v3.0?
File-based long-term AI memory system with BGE-M3 vector search, metadata filtering, compound scoring, graph-based neighbor expansion, and automated memory m... It is an AI Agent Skill for Claude Code / OpenClaw, with 54 downloads so far.
How do I install Z1 Memory Palace v3.0?
Run "/install z1-memory-palace" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Z1 Memory Palace v3.0 free?
Yes, Z1 Memory Palace v3.0 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Z1 Memory Palace v3.0 support?
Z1 Memory Palace v3.0 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Z1 Memory Palace v3.0?
It is built and maintained by z1one0415 (@z1one0415); the current version is v3.0.0.
More Skills