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Agent Skill · 研究检索

podcast-radar-cn(播客雷达 CN)

podcast-radar-cn 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

podcast-radar-cn 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 32,156。

总安装 2,569周安装 106GitHub Stars 公开资料未说明下载 840核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
0.1.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:podcast-radar-cn(播客雷达 CN)
来源仓库:https://github.com/cellinlab/podcast-radar-cn
安装命令:
openclaw skills install podcast-radar-cn
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install podcast-radar-cn

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

podcast-radar-cn 聚焦中文播客榜单,支持热门节目发现、创作者对比与策展列表生成。适用于内容研究者、媒体机构或品牌方寻找行业趋势与合作机会。提供播放量、增长率与听众画像等多维度数据分析辅助决策。数据来源依赖第三方排行榜更新频率,可能存在延迟或不完整情况。

商业用途引用节目信息时请遵守版权协议注明出处与授权范围。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install podcast-radar-cn;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

podcast-radar-cn 怎么安装?

在终端执行 openclaw skills install podcast-radar-cn。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

podcast-radar-cn 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

podcast-radar-cn 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

podcast-radar-cn 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

podcast-radar-cn 用的人多吗?

公开数据是累计安装 2,569 次,近一周安装 106 次,下载 840 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

podcast-radar-cn 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
podcast-radar-cn

播客雷达 CN · 本页

2,569—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
podcast-radar-cn
description
Discover, compare, and curate trending Chinese podcasts or episodes from 中文播客榜. Use for hot or recent show discovery, creator benchmarking, curation lists, competitor research, or podcast distribution leads. Prefer ranking fields and title signals first, and only do small-scale Xiaoyuzhou enrichment when needed.
homepage
https://github.com/XiaohuoluFM/xhlfm-skills/tree/main/skills/podcast-radar-cn
metadata
{"openclaw":{"emoji":"🎙️","homepage":"https://github.com/XiaohuoluFM/xhlfm-skills/tree/main/skills/podcast-radar-cn","requires":{"anyBins":["python3","python"]},"install":[{"id":"brew-python","kind":"brew","formula":"python","bins":["python3"],"label":"Install Python 3 (brew)","os":["darwin"]}]}}

Podcast Radar CN

Use this skill when the user wants to discover, compare, or curate Chinese podcasts or podcast episodes based on current ranking data.

This skill is strongest at:

  • listener discovery
  • creator benchmarking
  • curation and distribution research

It is not a general web scraping skill. Its default posture is ranking-first and title-first.

Skill Root Rule

Treat the directory containing this SKILL.md as the skill root.

  • In OpenClaw, prefer {baseDir} when calling files inside this skill.
  • In other hosts or manual installs, use the same paths relative to the skill root, for example scripts/fetch_xyz_rank.py.
  • Examples below use python3; if the host only exposes python, swap the binary name.

Quick Start

Choose one of the four ranking lists:

  • hot-episodes
  • hot-podcasts
  • new-podcasts
  • new-episodes

Fetch a candidate set first:

python3 {baseDir}/scripts/fetch_xyz_rank.py --list hot-episodes --limit 20

Filter by genre, freshness, or query when the user already has a direction:

python3 {baseDir}/scripts/fetch_xyz_rank.py \
  --list new-episodes \
  --limit 12 \
  --genre 社会与文化 \
  --freshness-days-max 30

If and only if you truly need extra context for a small set of candidates, enrich a few Xiaoyuzhou URLs:

python3 {baseDir}/scripts/enrich_xiaoyuzhou.py \
  --episode-url https://www.xiaoyuzhoufm.com/episode/69bf524c2d318777c9169361

Workflow

  1. Classify the request as one of:

- listener discovery - creator benchmarking - curation/distribution research

  1. Interpret the user's wording before choosing the list:

- if the user says 热门播客, 最近播客, 值得听的播客, or similar casual Chinese phrasing, default to episode-level results - if the user explicitly asks for 播客频道, 播客栏目, 节目主页, show-level, 频道级, or wants a creator benchmark list, use podcast-level results

  1. Pick the most relevant ranking list.

- default listener-discovery wording usually maps to hot-episodes or new-episodes - explicit channel / show / benchmark wording usually maps to hot-podcasts or new-podcasts

  1. Fetch enough candidates to support filtering; do not stop at the first 5 unless the user asked for 5.
  2. Use ranking fields and title signals first.
  3. Only if the answer would otherwise be weak, enrich a small set of Xiaoyuzhou pages.
  4. Return a task-shaped result, not raw JSON.

Query Interpretation Rule

In Chinese product usage, users often say 播客 when they really mean 最近值得点开的内容.

Default behavior:

  • 热门播客
  • 最近热门播客
  • 最近值得听的播客
  • 推荐几个热门播客

Treat these as requests for episode-level recommendations unless the wording clearly asks for show/channel-level objects.

Switch to podcast-level results only when the user explicitly asks for things like:

  • 播客频道
  • 播客栏目
  • 播客节目主页
  • 频道级榜单
  • 栏目级榜单
  • show-level benchmark or channel list

When in doubt:

  • listener-oriented wording -> episode-first
  • benchmark / channel / host / show-portfolio wording -> podcast-first

Title-First Rule

Before reaching for Xiaoyuzhou pages, inspect:

  • title
  • podcastName / name
  • primaryGenreName
  • rank
  • playCount / avgPlayCount
  • commentCount / avgCommentCount
  • freshness fields

The fetch script also extracts title signals such as:

  • episode markers like S8E9, EP03, Vol132
  • guest hints like A×B, 对话某某
  • format hints like 对谈, 访谈, 复盘, 盘点
  • topic keywords inferred from the title

If those signals are enough, do not enrich.

Read references/title-signals.md when you need examples or interpretation guidance.

Xiaoyuzhou Enrichment Rule

Xiaoyuzhou enrichment is allowed only for narrow, necessary follow-up work.

Hard rules:

  • never bulk-enrich by default
  • never enrich just to complete every field
  • never enrich more than 20 URLs in one run
  • if a request implies short-window bulk access, refuse enrichment and stay at ranking level

Use enrichment when:

  • a short list needs better recommendation reasons
  • you need the real Xiaoyuzhou pid from an episode page
  • you need a podcast brief or episode description for a handful of finalists

The enrichment script enforces the cap for you.

Output Modes

Use one of these result shapes:

  • Listener Discovery: what episode is worth hearing now, and why
  • Creator Benchmarking: which shows are worth studying or comparing against
  • Curation and Distribution: which shows or episodes are worth packaging, recommending, or developing into downstream ideas

Read references/output-modes.md when you need concrete formatting guidance.

Data Caveats

  • 中文播客榜 is weekly, not minute-by-minute real time
  • the data is not full-platform coverage
  • primaryGenreName is often missing on new lists
  • openRate / avgOpenRate can exceed 1; treat these as internal ranking signals, not literal rates

Read references/api.md when you need field notes or endpoint details.

Scripts

  • scripts/fetch_xyz_rank.py

Purpose: fetch and normalize ranking data, with basic filters and title-signal extraction

  • scripts/enrich_xiaoyuzhou.py

Purpose: enrich a small set of Xiaoyuzhou pages with brief/description/shownotes context, under a strict cap

What To Avoid

  • dumping raw fields without synthesis
  • pretending the ranking is a real-time universal truth
  • using Xiaoyuzhou enrichment for large-page traversal
  • over-explaining openRate as if it were a clean probability

平台分布

OpenClaw

71.07%
按下载量换算597

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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