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podcast-radar-cn播客雷达 CN

Agent Skill

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。

总安装

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周安装

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GitHub Stars

公开资料未说明

下载量

840
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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