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Lizhi
by
mikeclaw007
· GitHub ↗
· v0.1.0
· MIT-0
160
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install lizhi
Description
提供荔枝FM公开节目及播客数据摘要、榜单统计和搜索结果，支持关键词检索和节目表现对比分析。
README (SKILL.md)
荔枝FM
用途与边界
- 面向公开节目/播客页的检索与表现数据摘要
- 不提供下载、接口逆向或突破风控能力
- 仅用于公开页面的轻量分析与提醒
关键入口
- 主页：https://www.lizhi.fm/
- 分类/榜单：站点入口
- 搜索入口：站内搜索
常见任务
- 指定关键词/分类的节目列表摘要（播放量、收藏、评论）
- 播客主页近期节目表现对比
- 榜单条目分布与题材统计
数据字段
- 节目名称、播客名称、时长、发布时间、播放量/收藏/评论、链接
- 播客主页链接、近期节目交互指标摘要
- 榜单名称、采集时间、来源链接
自动化要点
- 动态渲染与人机校验，建议人工打开后触发解析
- 请求频率需控制，不进行批量抓取
- 不进行下载或接口调用
示例流程
- 关键词摘要：输入关键词 → 搜索 → 抽取条目 → 输出表现摘要
- 播客对比：访问主页 → 抽取近期节目 → 输出交互指标
- 榜单统计：访问榜单 → 抽取条目 → 题材分布统计
合规提示
- 遵守平台规则，不进行下载、接口调用或批量采集
- 结果仅用于内部分析与提醒
Usage Guidance
This skill is instruction-only and appears coherent with its purpose. Before installing: (1) know it will access external public Lizhi.fm pages when invoked — ensure you're comfortable with the agent loading those URLs; (2) it explicitly avoids credentials and bulk scraping, but monitor usage to avoid accidental high-rate requests or terms-of-service violations; (3) dynamic pages or CAPTCHA challenges may require manual intervention as the SKILL.md suggests; and (4) if you later need automated API access or broader data collection, expect additional permissions/credentials and re-evaluate then.
Capability Analysis
Type: OpenClaw Skill
Name: lizhi
Version: 0.1.0
The skill bundle consists of metadata and instructions (SKILL.md) for an AI agent to perform lightweight analysis of public podcast data on Lizhi FM. It contains no executable code, and the instructions explicitly emphasize compliance with platform rules, prohibiting data scraping, downloading, or bypassing security measures.
Capability Assessment
Purpose & Capability
Name/description (public Lizhi FM summaries, rankings, search) match the SKILL.md instructions. No unrelated env vars, binaries, or installs are requested.
Instruction Scope
Instructions limit work to public pages, list the data fields to extract, advise against downloads, API reverse-engineering, or bulk scraping, and recommend human-assisted handling for dynamic rendering and CAPTCHAs. They do not instruct reading local files or accessing unrelated credentials.
Install Mechanism
No install spec or code is present (instruction-only), so nothing will be written to disk or fetched during install.
Credentials
The skill declares no required environment variables, credentials, or config paths; the requested scope is proportionate to the stated tasks.
Persistence & Privilege
always is false and the skill has no special persistence or system-wide configuration changes; autonomous invocation is the platform default and is not otherwise elevated here.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install lizhi - After installation, invoke the skill by name or use
/lizhi - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
lizhi-hot-trend v0.1.0
- Initial release registered skill for 荔枝FM (Lizhi FM) trending podcast and program analysis.
- Supports keyword/category summaries, recent show performance comparisons, and chart/topic distribution stats.
- Only works with publicly accessible pages; does not enable downloads, interface reverse engineering, or bypassing site restrictions.
- Provides quick data summaries—including play counts, favorites, comments, and episode/item info.
- Designed for lightweight, compliant internal use and reminders.
Metadata
Frequently Asked Questions
What is Lizhi?
提供荔枝FM公开节目及播客数据摘要、榜单统计和搜索结果，支持关键词检索和节目表现对比分析。 It is an AI Agent Skill for Claude Code / OpenClaw, with 160 downloads so far.
How do I install Lizhi?
Run "/install lizhi" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Lizhi free?
Yes, Lizhi is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Lizhi support?
Lizhi is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Lizhi?
It is built and maintained by mikeclaw007 (@mikeclaw007); the current version is v0.1.0.
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