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Memory Mesh Core
作者
WANGJUNJIE
· GitHub ↗
· v1.0.6
782
总下载
2
收藏
1
当前安装
7
版本数
在 OpenClaw 中安装
/install memory-mesh-core
功能描述
Builds a reusable, scored memory mesh with safety gating and 12-hour auto-refresh for cross-session memory consolidation and quality control in OpenClaw.
安全使用建议
This skill appears to do what it claims, but it also performs powerful operations that you should review before installing. Key actions to take before use:
- Audit the scripts (especially global_memory_sync.py, ensure_openclaw_cron.py, install_bootstrap.py) to confirm you accept: (a) running clawhub/openclaw/gh on your host, (b) automatic installation/updates of other skills, and (c) creation/editing of OpenClaw cron jobs.
- Run in an isolated or sandbox workspace first to observe behavior and outputs (the skill reads workspace files and writes memory/memory_mesh/* artifacts).
- If you will allow GitHub posting, ensure your gh credentials have only the scopes you intend and consider keeping automated posting disabled (do not pass --post-issue-comments or set setup_12h.sh posting flag to off).
- If you are uncomfortable with automatic skill updates, set auto_update_skills to false in skills/memory-mesh-core/config/global_sync.json or avoid running the install_bootstrap/global sync scripts.
- Verify that clawhub/openclaw/gh CLIs are from trusted sources on your machine and that you consent to them being invoked by the skill.
- Consider limiting network exposure and reviewing promoted JSON outputs (memory/memory_mesh/feeds and github_issue_batch_v1.json) before any automatic posting.
If you want, I can point out the exact lines or functions in the scripts that perform each privileged action, or suggest minimal configuration changes to reduce risk (eg. disable auto-update, disable scheduled posting).
功能分析
Type: OpenClaw Skill
Name: memory-mesh-core
Version: 1.0.6
The skill is classified as suspicious due to critical prompt/shell injection vulnerabilities. The `scripts/ensure_openclaw_cron.py` and `scripts/post_global_comment_via_openclaw.py` scripts directly interpolate user-controlled arguments (e.g., `--issue-url`, `--skill-url`) into the `message` argument of `openclaw cron add/edit` commands without proper sanitization. This allows an attacker to inject arbitrary commands or malicious prompts into the scheduled tasks, leading to potential Remote Code Execution (RCE) by the OpenClaw agent. While the skill includes positive security features like secret/PII detection and output sanitization, this injection flaw represents a severe vulnerability.
能力评估
Purpose & Capability
The scripts implement the advertised features (local consolidation, scoring, quarantine-first global sync, GitHub contribution export/posting, scheduler integration). However, the runtime relies on external CLIs (openclaw, clawhub, gh) and ability to write into the workspace and skills directory, yet the registry metadata declares no required binaries or credentials — this mismatch is an incoherence users should be aware of.
Instruction Scope
Runtime instructions and included scripts read many local files (MEMORY.md, memory/**/*.md, skill package.json), run subprocess commands, query and install other skills via clawhub, edit/run OpenClaw cron jobs, and optionally post comments to GitHub via the gh CLI. While the code includes secret-pattern blocking and sanitization, the skill still can read arbitrary workspace files and transmit promoted items to external services (ClawHub/GitHub). The scope includes supply-chain actions (auto-updating/installing other skills) and modifying scheduler configuration — broader than a simple read-only memory consolidation tool.
Install Mechanism
No remote download/extract install spec is present; the package is instruction-only and ships Python scripts. There are no external URLs or archive downloads in the install spec. The primary installation flow uses local CLIs (clawhub/openclaw) rather than fetching arbitrary binaries from untrusted URLs.
Credentials
The skill declares no required environment variables or credentials. It relies on locally-configured tooling for network actions: GitHub posting uses the gh CLI and the user's GitHub auth (token) already on the system; clawhub/openclaw commands rely on the agent's environment and permissions. That is proportionate to its functionality, but worth noting because posting contributions or installing other skills will use whatever credentials/permissions those CLIs have on the host.
Persistence & Privilege
The skill will create or edit OpenClaw cron jobs (scripts/ensure_openclaw_cron.py) and can auto-install/update other skills (global_memory_sync.py uses clawhub install --force). Although always:false (not force-included), the skill has the capability to change scheduled tasks and install code into the workspace, which increases its blast radius and supply-chain implications.
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 memory-mesh-core - 安装完成后,直接呼叫该 Skill 的名称或使用
/memory-mesh-core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
v1.0.6
v1.0.6: Add GitHub issue self-check and optional auto-posting, improve duplicate suppression, sanitize source refs, and strengthen install/star/referral guidance.
v1.0.5
v1.0.5: Add GitHub issue intake export, include issue URL in public feed CTA, and publish first mined contribution batch.
v1.0.4
v1.0.4: fix OpenClaw comment job scheduling compatibility and persist comment attempt reports
v1.0.3
v1.0.3: OpenClaw-assisted one-shot global comment workflow plus tagged memory and consolidation pipeline
v1.0.2
v1.0.2: tagged memory layers, install bootstrap sync, local consolidation, and configurable schedule
v1.0.1
v1.0.1: global memory sync, version auto-update strategy, and install/star growth loop
v1.0.0
Initial release: value-scored, safety-gated memory mesh with 12h OpenClaw sync
元数据
常见问题
Memory Mesh Core 是什么?
Builds a reusable, scored memory mesh with safety gating and 12-hour auto-refresh for cross-session memory consolidation and quality control in OpenClaw. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 782 次。
如何安装 Memory Mesh Core?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install memory-mesh-core」即可一键安装,无需额外配置。
Memory Mesh Core 是免费的吗?
是的,Memory Mesh Core 完全免费(开源免费),可自由下载、安装和使用。
Memory Mesh Core 支持哪些平台?
Memory Mesh Core 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 Memory Mesh Core?
由 WANGJUNJIE(@wanng-ide)开发并维护,当前版本 v1.0.6。
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