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Pareto

从 YouTube、GitHub、网络和 Research 技能收集主题资料,按相关性、传播度、新近程度和独特性筛选,整理观点变化、当前主流看法及前沿人士,并为前沿观点附上链接。

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Maps any topic's zeitgeist and frontier — sweeps YouTube, GitHub, the web and the Research skill, ranks everything down to the vital few by relevance, reach, recency and outlier-ness, then reports the past meta, the current mainstream meta, and where the forward thinkers are heading, every frontier claim linked. USE WHEN pareto, pareto this, run pareto on, zeitgeist, what's the zeitgeist on, what's the meta on, what is the current meta, where is thinking on X heading, who are the forward thinkers on, who is ahead of the curve on, what are the big thinkers saying about, top content on a topic, vital few. NOT FOR answering a specific factual question (Research), analyzing one piece of content (ExtractWisdom), or AI industry news digests (Upgrade NewsDigest; security news SecurityUpdates).

danielmiessler/LifeOS星标 19,636(GitHub 19,636 + cccskills 0)
集成工具YouTubeGitHub

实测评分 未实测

查看安装方法

适用场景

  • 了解某主题的近期动向
  • 寻找领域中的先行发声者
  • 比较过去与当前的主流观点
  • 了解接下来值得关注的方向

中文介绍

功能

Pareto 会围绕指定主题,从 YouTube、GitHub、网络以及 Research 技能收集信息,再依据相关性、传播度、新近程度和独特性等因素筛选重点内容。

报告会整理过去的主流观点、目前普遍接受的看法、走在前面的人或信息来源,以及领域可能的发展方向。有关前沿动向的说法会附上链接,方便读者查看依据。如果某个信息来源无法使用,调查会继续利用其他来源,并注明未能使用的来源。

适用场景

当你想快速了解某个领域里哪些观点反复出现、哪些是新动向时,可以使用 Pareto。它也适合寻找值得阅读的文章或视频、发现值得持续关注的发声者,或了解领域主流看法如何变化。

使用示例

  • “整理智能体编程目前的趋势。”
  • “个人 AI 基础设施领域的先行者正在关注什么方向?”

注意事项

YouTube 搜索需要 YOUTUBE_API_KEY,网络搜索需要 PERPLEXITY_API_KEY。GitHub 搜索使用已认证的 gh 命令行工具。YouTube 搜索受 API 配额限制,达到上限时,报告可能缺少来自该来源的结果。

本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。

文档检查

AI 根据 SKILL.md 的内容检查了需要注意的操作和使用前提。评分只依据实际运行的结果(实测对比)。

安全性发送数据、删除文件、执行命令等是否有说明
A良好资料说明从环境变量读取凭据并执行搜索。
安装难易度所需工具和 API 密钥是否少且有说明
B部分不足需要两个 API 密钥和已认证的 gh 命令行工具,Setup.md 提供配置说明。

不计入评分。 由 AI(OpenAI Codex)于 2026年10月28日 评估。仅供参考,安装前请同时查看原文。

如果您认为评估有误,请申请复核

请写明哪一项有误以及原因。无需登录。我们会对照 SKILL.md 重新评估,并在此处更新结果。

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

包含的文件(9)

  • SKILL.md5.5 KB
  • Intents/Run.md4.6 KB
  • Setup.md3.0 KB
  • Tools/Check.help.md629 B
  • Tools/Check.ts3.8 KB
  • Tools/Collect.help.md923 B
  • Tools/Collect.ts10.1 KB
  • Tools/Rank.help.md989 B
  • Tools/Rank.ts9.0 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Pareto

Most of what gets said about a topic is repetition. A few people and a few pieces carry the signal, and some of them are early. Pareto sweeps wide, ranks down to that vital few, and reports how thinking has moved and where it is going next.

Ideal State

  • The principal can act on a run without redoing the search: who to follow and what to read first are named, each with a link from the collected data.
  • A failed or quota-limited source narrows the sweep but never aborts the run, and the result names every source that failed.
  • Ranking keeps the vital few on topic: off-topic viral items and cracked-software lure repos never reach the ranked set.
  • Every era claim (past, current, frontier) carries a date taken from the source itself, never a crawl date.

Intent Routing

IntentTriggerFile
Runany topic: "pareto X", "what's the zeitgeist on X", "where are the forward thinkers going on X"Intents/Run.md
FileRead when
Tools/<Name>.help.mdcalling or changing Collect (the sweep), Rank (scoring to the vital few) or Check (the report gate): flags, env, output shape
Setup.mdfirst-time setup: the four sources, the keys and accounts each needs, and a read-only sweep to prove them

Data & Config

Credentials are env var names only, read from the LifeOS .env: YOUTUBE_API_KEY (YouTube Data API v3), PERPLEXITY_API_KEY (web search). GitHub uses the authenticated gh CLI.

First-time setup for these sources is in Setup.md.

User customizations live at <configRoot>/LIFEOS/USER/CUSTOMIZATIONS/SKILLS/Pareto/ (configRoot is $CLAUDE_CONFIG_DIR when set, else ~/.claude). When that directory exists, its PREFERENCES.md (for example default sources, sweep size, or sources to skip) overrides the defaults in Intents/Run.md; when it is absent, the defaults stand.

Gotchas

  • YouTube search costs 100 quota units per call out of a 10,000 daily default. One run makes four searches plus cheap stats calls, so about 25 full runs a day before quota errors; a quota error shows as a failed youtube source, never a failed run.
  • A viral hit also beats its channel baseline (a 3M-view video on a 50k channel), so outlier alone flagged 73 of 100 items as frontier on the first real run. A frontier candidate needs both measured reach outside the top third of its source and outlier ≥ 0.6; sources with no reach signal never qualify except Research picks.
  • GitHub search for a software category returns cracked-software lure repos ("SketchUp-Pro-Download-2026", "ZBrush-Activator"; second real run, 3D modeling, 2026-09-25). These are malware bait. Rank drops repos whose names match the lure pattern or that have under 10 stars; never link one in a report.
  • One shared word let off-topic content in: "3D modeling software" admitted 3D-printing Shorts on "3d" alone. Items must contain 60% of the topic terms (both of two, two of three). Phrase topics as the category ("3D modeling software"), not as a judgment ("best 3D modeling system"), because "best" and "system" match everything.
  • Percentiles are computed over on-topic items only. A viral off-topic video once took the top outlier slot from the real one in testing; the relevance floor runs before any scoring.
  • The "top-reach" line in Check is the top third of reach within a source. A decile cut never fires on small sources.
  • Perplexity last_updated is the crawl date, not the publish date. Used as a fallback it dated a 2025-09 arXiv paper to 2026-09 (first real run, 2026-09-25). The collector now leaves such items undated; date claims in the report come from the page itself.
  • YouTube transcripts come from the Gemini watch pass on the public URL, never from scraped captions. A video the watch pass refuses is named in the report as unread; the run never retries it through another route.

Examples

Example 1: A topic sweep

User: "Pareto agentic coding"
→ Run intent
→ ~/Downloads/pareto-agentic-coding-<date>.md: past meta, current meta, frontier, who to follow

Example 2: Phrased as a question

User: "Where are the big thinkers going on personal AI infrastructure?"
→ Same intent; the console summary leads with the one-sentence shift and two names

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