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在 OpenClaw 中安装
/install self-track
功能描述
Sig Botti's self-improvement tracking system. Use when (1) learning something new, (2) noticing a gap in capabilities, (3) completing a self-improvement task...
安全使用建议
This skill is mostly a set of personal workflow instructions, but it refers to local scripts and tools that are not included or declared. Before using or allowing an agent to run these steps: (1) verify that the referenced scripts exist and inspect their contents (scripts/ollama_mem.py, the openclaw skill-creator script) — do not run unknown scripts; (2) ensure you understand where vector/embedding data would be sent (Ollama/nomic) and whether any API keys or external services are involved; (3) be cautious about running commands that write into system paths (e.g., /usr/local/lib/node_modules) or that auto-create skills—these can modify your environment; (4) if you want to install or use this skill, ask the author to include missing scripts or to explicitly declare required binaries and environment variables so you can audit them. If you need a safer evaluation, provide the missing scripts or a clearer dependency list so this assessment can be upgraded.
功能分析
Type: OpenClaw Skill
Name: self-track
Version: 1.0.0
The skill bundle defines a structured workflow for an agent to track its own learning progress, capability gaps, and memory updates. It utilizes local markdown files (e.g., memory/gaps.md) and local scripts (scripts/ollama_mem.py) to manage a vector database via Ollama. No indicators of data exfiltration, malicious execution, or unauthorized persistence were found; the instructions are consistent with the stated purpose of self-improvement tracking.
能力评估
Purpose & Capability
The skill's stated purpose is personal self-tracking (gaps, lessons, weekly reviews). The instructions go beyond that by referencing: (1) Ollama/nomic embedding usage, (2) python scripts (scripts/ollama_mem.py) that are not included, and (3) an openclaw skill-creator script under /usr/local/lib/node_modules/... which would create skills on the host. These referenced capabilities are not declared in the manifest (no dependencies, no env vars) and some (skill creation) are not necessary solely for tracking progress.
Instruction Scope
Runtime instructions tell the agent/user to read and write files under memory/, run local python scripts, call an embedding backend (Ollama/nomic), and run openclaw CLI commands (openclaw cron list). The SKILL.md assumes presence of specific scripts and system paths that are not provided and could cause the agent to attempt filesystem or network actions outside the simple tracking purpose.
Install Mechanism
This is instruction-only with no install spec and no code files included. That lowers installation risk (nothing will be automatically downloaded or written by an installer).
Credentials
The manifest declares no required environment variables or credentials, but the instructions reference an embedding stack (Ollama/nomic) which in some setups may require configuration or credentials. The SKILL.md also references python3 and openclaw tooling but doesn't declare them as requirements. The absence of declared env/dependency requirements is a mismatch with the instructions.
Persistence & Privilege
The skill does not set always:true and requests no declared persistent privileges. However, the instructions guide the user/agent to run a skill-creator script in /usr/local/lib/node_modules and to commit files (write to skills/ and memory/). That implies filesystem writes and potential creation of new skills, which expands the effective write scope beyond mere note-taking—this should be considered before granting execution rights.
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 self-track - 安装完成后,直接呼叫该 Skill 的名称或使用
/self-track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
v1.0.0
Initial release: self-improvement tracking for Sig Botti
元数据
常见问题
self-track 是什么?
Sig Botti's self-improvement tracking system. Use when (1) learning something new, (2) noticing a gap in capabilities, (3) completing a self-improvement task... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 102 次。
如何安装 self-track?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install self-track」即可一键安装,无需额外配置。
self-track 是免费的吗?
是的,self-track 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
self-track 支持哪些平台?
self-track 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 self-track?
由 luke(@louch84)开发并维护,当前版本 v1.0.0。
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