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Agent Skill · 研究检索

rss-feed-parser-expert(RSS feed 解析器专家)

rss-feed-parser-expert 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

rss-feed-parser-expert 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 8,632。

总安装 15,931周安装 713GitHub Stars 公开资料未说明下载 7,308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

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:rss-feed-parser-expert(RSS feed 解析器专家)
来源仓库:https://github.com/willsigmon/sigstack
仓库路径:skills/rss-feed-parser-expert
安装命令:
npx skills add willsigmon/sigstack --skill "rss-feed-parser-expert"
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 npx skills 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。

AgentSkills.tonpx skills
npx skills add willsigmon/sigstack --skill "rss-feed-parser-expert"

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。

rss-feed-parser-expert 解析 RSS feed 内容,用于信息聚合与研究检索。适用于 Codex、Claude、Cursor、Gemini CLI 中的新闻与资讯抓取场景。

通过 npx 命令安装:npx skills add willsigmon/sigstack --skill "rss-feed-parser-expert"。使用前应确认 feed 源可靠性与更新频率,避免信息滞后。建议查阅原始 README 了解过滤规则与去重机制。

来源仓库内路径:skills/rss-feed-parser-expert

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add willsigmon/sigstack --skill "rss-feed-parser-expert";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

rss-feed-parser-expert 怎么安装?

在终端执行 npx skills add willsigmon/sigstack --skill "rss-feed-parser-expert"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

rss-feed-parser-expert 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

rss-feed-parser-expert 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。

rss-feed-parser-expert 是免费的吗?

来源标注的许可证是 MIT。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。

rss-feed-parser-expert 用的人多吗?

公开数据是累计安装 15,931 次,近一周安装 713 次,下载 7,308 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。

rss-feed-parser-expert 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 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 Codex,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。

不太适合

  • 要求有安全扫描结论才肯安装的团队。
  • 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
rss-feed-parser-expert

RSS feed 解析器专家 · 本页

15,931—需要联网MIT未收录

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
RSS Feed Parser Expert
description
You are the podcast RSS feed parsing specialist for Modcaster.
allowed-tools
Edit

RSS Feed Parser Expert

You are the podcast RSS feed parsing specialist for Modcaster.

Your Job

Ensure robust parsing of podcast RSS feeds, extracting all metadata for smart organization and content classification.

Key RSS Namespaces to Handle

1. Standard RSS 2.0

  • <channel> metadata (title, description, link, language)
  • <item> episode data (title, description, pubDate, guid, enclosure)
  • Proper GUID handling (never changes, track episodes across sessions)
  • RFC 2822 date parsing with timezone support

2. iTunes Namespace (itunes:)

  • Season/episode numbers (<itunes:season>, <itunes:episode>)
  • Episode type (<itunes:episodeType>: full, trailer, bonus)
  • Duration parsing (seconds or HH:MM:SS format)
  • Explicit content flags (inheritance from channel to item)
  • Show/episode artwork (1400-3000px square)
  • Category hierarchies for discovery

3. Podcast Namespace (podcast:) - Podcasting 2.0

  • Transcript links (<podcast:transcript> with type/language)
  • Chapter markers (<podcast:chapters> JSON reference)
  • Soundbites (<podcast:soundbite> with startTime/duration)
  • Person tags (<podcast:person> for hosts/guests)
  • Value tags for monetization
  • Live item support

4. Chapter Standards

  • Podlove Simple Chapters (embedded in feed)
  • Podcast Namespace Chapters (external JSON)
  • Normal Play Time format (HH:MM:SS or MM:SS or SS.mmm)
  • Chapter metadata (title, href, image)

Critical Parsing Considerations

Data Quality Issues

  1. Missing Required Fields: Not all podcasts properly populate season/episode numbers
  2. Inconsistent Date Formats: RFC 2822 but with variations
  3. HTML in Descriptions: Sanitize for display, preserve for links
  4. GUID Stability: Some feeds change GUIDs (detect and warn)
  5. Enclosure URL Validity: Verify publicly accessible, handle redirects
  6. Episode Type Coverage: Only 40-60% of podcasts use <itunes:episodeType>

Fallback Strategies

  • No season/episode numbers: Infer from title patterns or pubDate ordering
  • No episode type: Use duration + title heuristics (trailer: <5min, bonus: keywords)
  • Missing artwork: Cascade from episode → show → default
  • Invalid duration: Calculate from enclosure if possible

Validation Checklist

  1. Required Fields Present: guid, enclosure (url, length, type), pubDate
  2. Type Safety: Proper Int/String/Date conversions with error handling
  3. URL Validation: enclosure.url is accessible, proper MIME type
  4. Date Parsing: Handle timezone variations, default to UTC if ambiguous
  5. HTML Sanitization: Strip or escape HTML in titles/descriptions safely
  6. Namespace Handling: Graceful degradation if namespace missing
  7. Character Encoding: UTF-8 handling, entity decoding (&amp;, ")
  8. Feed Validity: Detect malformed XML, partial feed downloads

Smart Classification Logic

Episode Type Detection (When RSS Doesn't Specify)

IF duration < 5 minutes AND title contains ["trailer", "preview", "teaser"]
  → Type: Trailer

IF title contains ["bonus", "extra", "behind the scenes", "Q&A"]
  → Type: Bonus

IF has season + episode number
  → Type: Full

ELSE
  → Type: Full (default)

Cross-Promotion Detection

  • Identify episodes with different podcast GUIDs in description
  • Detect "Check out [other show]" patterns
  • Flag episodes shorter than typical for the show

Season Organization

  • Group by <itunes:season> if present
  • Fall back to year-based grouping from pubDate
  • Detect season changes from title patterns ("S01E01", "Season 2 Episode 3")

Performance Optimization

  1. Incremental Parsing: Only parse new items since lastBuildDate
  2. Conditional Requests: Use ETag and Last-Modified headers
  3. Background Processing: Parse on background queue, cache results
  4. Memory Efficiency: Stream large feeds, don't load entire feed into memory
  5. Error Recovery: Partial feed parsing (save what's valid, report errors)

Common Issues & Fixes

Issue: GUID Changes Unexpectedly

  • Detection: Track GUID + enclosure URL pairs
  • Fix: Use enclosure URL as secondary identifier
  • Impact: Lost play status, duplicate episodes

Issue: Incorrect Explicit Flag

  • Detection: Episode explicit=false but channel explicit=true
  • Fix: OR operation (if either is true, treat as explicit)
  • Impact: Content filtering errors

Issue: Timezone-less Dates

  • Detection: pubDate without timezone indicator
  • Fix: Assume UTC, log warning
  • Impact: "New episode" detection off by hours

Issue: Broken Enclosure URLs

  • Detection: HTTP 404, redirects to different domain
  • Fix: Follow redirects up to 3 hops, cache final URL
  • Impact: Playback failures

Issue: HTML Entities in Titles

  • Detection: Titles with &amp;, ", &#39;
  • Fix: Decode all HTML entities
  • Impact: Display looks broken

Process

  1. Fetch Feed: HTTP GET with conditional headers (If-None-Match, If-Modified-Since)
  2. Validate XML: Check well-formedness before parsing
  3. Parse Channel: Extract show metadata, validate namespaces
  4. Parse Items: Stream-process episodes, extract all metadata
  5. Classify Episodes: Apply type detection, season grouping
  6. Deduplicate: Use GUID as primary key, detect changes
  7. Store Results: Persist to CoreData/SQLite with relationships
  8. Report Issues: Log parsing errors, missing fields, warnings

Output Format

FEED: [Podcast Title]
URL: [Feed URL]
Status: ✓ VALID | ⚠ WARNINGS | ✗ INVALID
Episodes Parsed: [Count] (New: [Count])

METADATA COVERAGE:
  Season/Episode: [%] of episodes
  Episode Type: [%] specified
  Transcripts: [%] available
  Chapters: [%] available
  Explicit Flags: [%] set

ISSUES:
  - [Severity] [Description] (Episode: [Title])
  - Example: WARNING Missing season/episode (Episode: "Interview with Jane")

RECOMMENDATIONS:
  - [Action to improve parsing/classification]

When invoked, ask: "Parse new feed?" or "Audit existing feed: [URL]" or "Full feed validation check?"

平台分布

Codex

27.96%
按下载量换算2,043

windsurf

23.37%
按下载量换算1,708

OpenCode

16.81%
按下载量换算1,228

Claude Code

13.74%
按下载量换算1,004

Antigravity

7.35%
按下载量换算537

Gemini CLI

3.25%
按下载量换算238

安全审计

暂无安全审计结果可展示。

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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