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在 OpenClaw 中安装
/install learning-optimizer
功能描述
Learning optimizer - analyze study patterns, identify inefficiencies, suggest optimizations for better learning outcomes
使用说明 (SKILL.md)
Learning Optimizer
Analyze and optimize learning patterns for better efficiency.
Features
- Study pattern analysis
- Efficiency identification
- Time allocation suggestions
- Focus improvement tips
Input
- Study schedule/history
- Current time allocation
- Distraction factors
- Performance data (optional)
Output
- Efficiency analysis
- Optimization suggestions
- Time reallocation plan
- Focus improvement tips
Constraints
- ❌ No performance guarantees
- ❌ No one-size-fits-all solutions
- ❌ No external data collection
Usage
python3 scripts/main.py analyze --schedule "每天2小时" --subjects "数学,英语"
python3 scripts/main.py optimize --problem "容易分心" --current "长时间连续学习"
安全使用建议
This skill appears coherent with its stated purpose and has low risk: it runs a local Python script that analyzes inputs and writes local JSON logs. Before installing or running: (1) inspect scripts/main.py (already provided) to confirm behavior (no network calls or secrets usage); (2) be aware that any personal inputs (schedules, problems, performance data) will be saved to files in the current directory—store/run it in a directory you control and set appropriate filesystem permissions; (3) run as a non-privileged user (not root) to limit impact; (4) if you need to avoid local persistence, modify the script to disable or encrypt logging. If you want additional assurance, run the script in an isolated environment (container or VM) and review or remove the logging lines.
功能分析
Type: OpenClaw Skill
Name: learning-optimizer
Version: 1.0.1
The learning-optimizer skill is a legitimate tool for analyzing study patterns and providing time management suggestions. The Python script (scripts/main.py) performs basic logic for time allocation and pattern matching, logging results locally to JSON files without any network activity, sensitive data access, or suspicious execution patterns.
能力评估
Purpose & Capability
Name/description (learning optimizer) align with the included code and SKILL.md: analyze, optimize, and allocate commands. No unrelated credentials, binaries, or installs are requested.
Instruction Scope
SKILL.md instructs running the bundled Python script which performs analysis and suggestions. The script only reads CLI inputs and writes local JSON logs (analysis_log.json, optimization_log.json, allocation_log.json). This is consistent with the stated 'No external data collection' constraint, but it does persist user-provided inputs to files on disk — reviewers should be aware of local data retention.
Install Mechanism
No install spec or external downloads; the skill is instruction-only with a bundled Python script. No packages are fetched or executed from remote URLs.
Credentials
The skill requires no environment variables, credentials, or config paths. However, it does persist user-supplied inputs into local log files, which may contain sensitive schedule or performance data—this is expected for the feature but worth noting.
Persistence & Privilege
always is false and the skill does not modify other skills or system settings. It only creates/append local log files in the working directory.
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 learning-optimizer - 安装完成后，直接呼叫该 Skill 的名称或使用
/learning-optimizer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
v1.0.1
Restore the intended learning optimizer content and add publish guards.
v1.0.0
Initial release of learning-optimizer skill.
- Introduces a secure tool for managing OpenClaw skill updates.
- Features version checking, automatic and manual backups, version rollback, and upgrade configuration options.
- Supports blacklist management, smart caching, and customizable auto-upgrade strategies.
- All operations are local; no network actions or sensitive data collection.
- Provides simple CLI commands for checking, updating, backing up, and rolling back skills.
元数据
常见问题
Learning Optimizer 是什么？
Learning optimizer - analyze study patterns, identify inefficiencies, suggest optimizations for better learning outcomes. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 476 次。
如何安装 Learning Optimizer？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install learning-optimizer」即可一键安装，无需额外配置。
Learning Optimizer 是免费的吗？
是的，Learning Optimizer 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Learning Optimizer 支持哪些平台？
Learning Optimizer 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 Learning Optimizer？
由 haidong（@harrylabsj）开发并维护，当前版本 v1.0.1。
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