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Ship Learn Next
作者
freegm866-design
· GitHub ↗
· v1.0.0
· MIT-0
787
总下载
0
收藏
6
当前安装
1
版本数
在 OpenClaw 中安装
/install ship-learn-next
功能描述
Transforms learning content into shippable, actionable plans by breaking lessons into concrete, small development cycles focused on building, reflecting, and...
安全使用建议
This is an instruction-only planning skill and is internally coherent and low-risk: it only needs the learning content you provide and will produce shippable iteration plans. Before installing or using it: (1) avoid pasting any sensitive/private content into the skill (credentials, proprietary code, PII); (2) note the minor metadata mismatch (ownerId differs in _meta.json) — if provenance matters to you, ask the publisher for clarification; and (3) if you expect the skill to fetch web content (YouTube transcripts, etc.), verify the agent or another skill will handle that — this skill itself only processes content you give it.
功能分析
Type: OpenClaw Skill
Name: ship-learn-next
Version: 1.0.0
The 'ship-learn-next' skill is a productivity tool designed to help users convert educational content (like transcripts or articles) into actionable project plans. The instructions in SKILL.md guide the agent to extract lessons and generate structured Markdown files, with no evidence of data exfiltration, malicious command execution, or harmful prompt injection.
能力评估
Purpose & Capability
The name, description, and SKILL.md content align: it transforms learning content into small shippable iterations. No binaries, env vars, or external services are requested, which is proportionate. Minor provenance inconsistency: registry metadata lists owner ID kn7338... while _meta.json ownerId is "softaworks" and source/homepage are unknown; this is a metadata/provenance oddity but does not change functionality.
Instruction Scope
Runtime instructions are narrowly scoped: read user-provided content, extract lessons, and produce rep-by-rep action plans. The skill does not instruct the agent to read unrelated system files, access environment variables, or send data to external endpoints. It asks to reference timestamps and source material (e.g., video minute X), which is appropriate for the purpose.
Install Mechanism
No install spec and no code files — instruction-only. This is lowest-risk from an install perspective (nothing is written to disk or downloaded).
Credentials
The skill requests no environment variables, credentials, or config paths. That is proportional to its stated functionality.
Persistence & Privilege
Flags show always:false and default autonomous invocation allowed. It does not request persistent presence or system-level changes. Autonomous invocation is the platform default and not a red flag here by itself.
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 ship-learn-next - 安装完成后，直接呼叫该 Skill 的名称或使用
/ship-learn-next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
Ship-Learn-Next v1.0.0
- Initial release of Ship-Learn-Next, a skill for turning passive learning content into actionable Ship-Learn-Next cycles.
- Guides users from educational content (transcripts, articles, tutorials) to concrete, shippable plans using the Ship → Learn → Next framework.
- Structures the process into clear steps: extract lessons, define goals, break down reps, map future iterations, and connect actions back to source material.
- Provides actionable output templates, key questions, and style guidance to ensure plans are specific, supportive, and action-oriented.
- Includes instructions for saving detailed plans in a consistent Markdown format and prompts for user accountability.
元数据
常见问题
Ship Learn Next 是什么？
Transforms learning content into shippable, actionable plans by breaking lessons into concrete, small development cycles focused on building, reflecting, and... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 787 次。
如何安装 Ship Learn Next？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install ship-learn-next」即可一键安装，无需额外配置。
Ship Learn Next 是免费的吗？
是的，Ship Learn Next 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Ship Learn Next 支持哪些平台？
Ship Learn Next 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 Ship Learn Next？
由 freegm866-design（@freegm866-design）开发并维护，当前版本 v1.0.0。
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