← 返回 Skills 市场
Mind-Wander
作者
jebadiahgreenwood
· GitHub ↗
· v0.1.0
· MIT-0
76
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install mind-wander
功能描述
Background reasoning agent that autonomously explores open questions using a local LLM (Qwen3.5-9B), a private knowledge graph for dead-end tracking, and Per...
安全使用建议
Key points to consider before installing:
- Missing declarations: The registry metadata says "no required env vars/config paths", but the code reads environment variables (WANDER_OLLAMA, FALKORDB_HOST/PORT, PERPLEXITY_API_KEY, OPENCLAW_WORKSPACE) and the installer reads ~/.openclaw/openclaw.json. Expect to provide or allow access to these if you run the installer.
- Installer side effects: install.sh will (unless you run with --dry-run or --skip-download) download a large GGUF model from a third-party Hugging Face repo and attempt to register a cron job on your OpenClaw gateway using a token in ~/.openclaw/openclaw.json. If you do not want the skill to create scheduled autonomous runs, do not allow it to access your gateway token; run the installer with --dry-run and perform manual cron registration instead.
- Missing helper: The installer references scripts/register_model.py but that file is not present in the provided manifest. Expect the automatic model registration step to fail unless you supply or author the missing script or run manual model registration.
- Sandbox is weak: The agent accepts arbitrary Python snippets and executes them via subprocess.run; the code blocks many obvious dangerous strings but runs the snippet in a plain Python subprocess without sandboxing (no chroot, no seccomp, no strict resource isolation beyond a timeout). Treat sandbox_run as potentially unsafe; run the skill only in an isolated environment (VM/container) if you will allow it to execute model-supplied code.
- Data access & exfiltration surface: The agent reads and writes workspace files (ON_YOUR_MIND.md, MENTAL_EXPLORATION.md, completions/). It also attempts network access to Ollama and Perplexity and reads ~/.openclaw/openclaw.json for tokens. If those files or services contain sensitive tokens/notes, the agent could read them. The skill does not declare those accesses in registry metadata.
Recommendations:
- Run a dry-run of install.sh first: bash install.sh --dry-run to see intended actions.
- Inspect the missing register_model.py or run model registration manually; avoid giving the installer gateway credentials. Use --skip-download if Ollama already has the model.
- If you want to test: run inside an isolated VM or container and ensure your real ~/ .openclaw/openclaw.json and other sensitive files are not mounted into the test environment.
- If you will grant gateway access, rotate the gateway token after install and audit the created cron job entry.
- If you need this capability but want less risk: ask the author for a version that does not attempt automatic gateway cron registration and that documents required env vars/config paths explicitly.
Given these mismatches, exercise caution and treat the skill as potentially intrusive until you either (a) run it in an isolated environment, or (b) confirm and restrict the installer's gateway/token access and review the missing helper scripts.
能力评估
Purpose & Capability
The skill's name/description (background reasoning with a local LLM, FalkorDB, Perplexity) matches the included code: it calls a local Ollama endpoint, queries FalkorDB, performs web searches, and writes findings to MENTAL_EXPLORATION.md. However, the skill claims no required environment variables or config paths in registry metadata, yet the code expects and reads several environment variables (OPENCLAW_WORKSPACE, WANDER_MODEL, WANDER_OLLAMA, FALKORDB_HOST/PORT, PERPLEXITY_API_KEY) and the install script reads ~/.openclaw/openclaw.json — these are relevant to its purpose but were not declared in the registry metadata (incoherent).
Instruction Scope
SKILL.md and the scripts instruct reading/writing workspace files (ON_YOUR_MIND.md, MENTAL_EXPLORATION.md, completions/), querying the user's FalkorDB, calling Perplexity, and running Python sandbox snippets. The installer also attempts to register a cron job with the OpenClaw gateway (via a token read from ~/.openclaw/openclaw.json). The instructions therefore touch user config files and the local gateway without declaring those requirements up-front — scope is broader than the registry metadata implies.
Install Mechanism
There is no registry 'install' block; instead an install.sh is provided. install.sh downloads a large GGUF model from a Hugging Face repo (a third-party repo id 'Jackrong/...'), installs Python packages, copies scripts into the user's workspace, initialises a wander graph, and tries to register a cron job via the gateway. Downloading large model artifacts from a non-official repo and programmatic registration of cron jobs are higher-friction operations and should be expected only for local-model skills — but the skill manifest didn't declare these install effects. Also the installer invokes scripts/register_model.py which is referenced but not present in the provided file manifest (inconsistency).
Credentials
The registry lists no required env vars, but the code reads/uses several env vars and config files: OPENCLAW_WORKSPACE, WANDER_MODEL/WANDER_OLLAMA, FALKORDB_HOST/PORT, PERPLEXITY_API_KEY, and ~/.openclaw/openclaw.json (to get gateway tokens or plugin API keys). The skill will also attempt to read the gateway token and post to the local gateway API. These credential/config accesses are not declared in the metadata and are privileged relative to the advertised purpose.
Persistence & Privilege
The skill installer attempts to create a recurring background job (30-minute cron entry) via the OpenClaw gateway using a token from ~/.openclaw/openclaw.json. That modifies the user's scheduled-task configuration and results in ongoing autonomous runs. While the skill itself is not marked always:true, the installer is designed to grant the skill persistent autonomous execution via the gateway. Installing thus grants scheduled autonomous execution and write access to workspace files; the manifest did not clearly surface this.
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 mind-wander - 安装完成后,直接呼叫该 Skill 的名称或使用
/mind-wander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. Autonomous background reasoning agent using Qwen3.5-9B, private FalkorDB wander graph for dead-end tracking, Perplexity web search, sandbox experiments, novelty gate. Produced first novel finding (cross-space routing robustness) in 10-minute test.
元数据
常见问题
Mind-Wander 是什么?
Background reasoning agent that autonomously explores open questions using a local LLM (Qwen3.5-9B), a private knowledge graph for dead-end tracking, and Per... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 76 次。
如何安装 Mind-Wander?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install mind-wander」即可一键安装,无需额外配置。
Mind-Wander 是免费的吗?
是的,Mind-Wander 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Mind-Wander 支持哪些平台?
Mind-Wander 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 Mind-Wander?
由 jebadiahgreenwood(@jebadiahgreenwood)开发并维护,当前版本 v0.1.0。
推荐 Skills