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hn-search搜索

Agent Skill

hn-search 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。

总安装

1,518

周安装

62

GitHub Stars

177

下载量

486
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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

unknown

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:hn-search(搜索)
来源仓库:https://github.com/dylanfeltus/skills
仓库路径:skills/hn-search
安装命令:
npx skills add https://github.com/dylanfeltus/skills --skill hn-search
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。

skills.shnpx skills
npx skills add https://github.com/dylanfeltus/skills --skill hn-search

简介

用于查找、检索和筛选相关信息。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

  • 适合根据关键词、任务场景或来源线索快速定位候选结果。
  • 通过 npx skills add 命令从指定仓库安装并使用。
  • 建议确认权限范围和维护状态,注意是否会触发联网或文件读写操作。
  • hn-search 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Hacker News Search

Search and monitor Hacker News stories, comments, and users via the Algolia HN Search API. No API key required.

When to Use

  • User asks about Hacker News discussions on a topic
  • User wants to find HN posts about a company, product, or technology
  • User wants to monitor HN for mentions of something
  • User asks "what's trending on HN" or "what did HN think about X"
  • User wants to find Show HN / Ask HN / Launch HN posts

API Overview

Base URL: https://hn.algolia.com/api/v1

Two search endpoints:

  • /search — Relevance-sorted (best for finding specific topics)
  • /search_by_date — Date-sorted (best for monitoring / recent activity)

Rate Limits: 10,000 requests/hour (generous, no auth needed)

How to Search

Step 1: Build the URL

https://hn.algolia.com/api/v1/search?query=QUERY&tags=TAG&hitsPerPage=N&numericFilters=FILTERS

Step 2: Fetch with web_fetch

Use web_fetch to call the API. Response is JSON.

Parameters

ParameterDescriptionExample
querySearch terms (URL-encoded)query=openai+gpt
tagsFilter by type (see below)tags=story
hitsPerPageResults per page (max 1000)hitsPerPage=20
pagePage number (0-indexed)page=0
numericFiltersNumeric filters (see below)numericFilters=points>100

Tag Filters

Use tags to filter by content type:

TagDescription
storyStories only
commentComments only
show_hnShow HN posts
ask_hnAsk HN posts
front_pageCurrently on front page
author_USERNAMEPosts by a specific user
story_IDComments on a specific story

Combine tags with commas (AND) or parentheses with commas (OR):

  • tags=story,show_hn → Show HN stories (AND)
  • tags=(story,comment) → Stories OR comments

Numeric Filters

FilterDescription
points>NMinimum points/upvotes
num_comments>NMinimum comments
created_at_i>TIMESTAMPAfter Unix timestamp
created_at_i<TIMESTAMPBefore Unix timestamp

Combine with commas: numericFilters=points>100,num_comments>50

Date Ranges

To search within a time window, use Unix timestamps with created_at_i:

Calculate the current Unix timestamp first (e.g., via exec: date +%s), then subtract:

WindowSubtract from now
Last 24 hours- 86400
Last 7 days- 604800
Last 30 days- 2592000

Example: if now is 1705312200, last 7 days = numericFilters=created_at_i>1704707400

Response Format

Each hit contains:

{
  "objectID": "12345",
  "title": "Story Title",
  "url": "https://example.com/article",
  "author": "username",
  "points": 150,
  "num_comments": 42,
  "created_at": "2024-01-15T10:30:00Z",
  "created_at_i": 1705312200,
  "story_text": "Text for Ask HN / Show HN (HTML)",
  "_tags": ["story", "author_username", "story_12345"]
}

For comments, hits also include:

{
  "comment_text": "The comment body (HTML)",
  "story_id": 12345,
  "story_title": "Parent Story Title",
  "story_url": "https://example.com",
  "parent_id": 12344
}

The response wrapper includes:

{
  "hits": [...],
  "nbHits": 1000,
  "page": 0,
  "nbPages": 50,
  "hitsPerPage": 20
}

Constructing HN Links

  • Story: https://news.ycombinator.com/item?id={objectID}
  • Comment: https://news.ycombinator.com/item?id={objectID}
  • User: https://news.ycombinator.com/user?id={author}

Step-by-Step Instructions

Searching for Stories on a Topic

  1. URL-encode the query
  2. Fetch: https://hn.algolia.com/api/v1/search?query=YOUR_QUERY&tags=story&hitsPerPage=10
  3. Parse the JSON response
  4. For each hit, present: title, points, num_comments, author, date, HN link, and original URL

Finding Recent/Trending Discussions

  1. Calculate Unix timestamp for your time window (e.g., 7 days ago)
  2. Fetch: https://hn.algolia.com/api/v1/search?query=YOUR_QUERY&tags=story&numericFilters=points>50,created_at_i>TIMESTAMP&hitsPerPage=10
  3. Sort results by points or comments for "trending"

Getting Comments on a Story

  1. Get the story's objectID from a search
  2. Fetch: https://hn.algolia.com/api/v1/search?tags=comment,story_STORYID&hitsPerPage=20
  3. Present comment_text, author, points for each

Monitoring a Topic (Show Recent Mentions)

  1. Use /search_by_date instead of /search
  2. Fetch: https://hn.algolia.com/api/v1/search_by_date?query=YOUR_QUERY&tags=(story,comment)&hitsPerPage=20
  3. Results are newest-first — useful for "what's new about X on HN"

Finding a User's Posts

  1. Fetch: https://hn.algolia.com/api/v1/search?tags=author_USERNAME,story&hitsPerPage=20
  2. For their comments: tags=author_USERNAME,comment

Output Format

Present results as a clean list:

### HN Results for "query" (N total)

1. **Story Title** (150 pts, 42 comments)
   By username · Jan 15, 2024
   🔗 https://example.com/article
   💬 https://news.ycombinator.com/item?id=12345

2. ...

For comments:

### HN Comments on "Story Title"

1. **username** (12 pts) · Jan 15, 2024
   > First ~200 chars of the comment text...
   💬 https://news.ycombinator.com/item?id=12345

Error Handling

  • Empty results: Tell the user no results were found. Suggest broadening the query or removing filters.
  • API error / timeout: Retry once. If still failing, inform the user the HN search API may be temporarily down.
  • Rate limited (429): Unlikely at 10k/hr, but if hit, wait 60 seconds and retry.
  • Malformed response: Check the URL construction — common issues are unencoded special characters in the query.

Examples

Example 1: "What's HN saying about Rust?"

Fetch: https://hn.algolia.com/api/v1/search?query=rust+programming&tags=story&hitsPerPage=5&numericFilters=points>50

Example 2: "Find Show HN posts about AI agents from the last month"

# Calculate timestamp for 30 days ago, then:
Fetch: https://hn.algolia.com/api/v1/search_by_date?query=ai+agents&tags=show_hn&numericFilters=created_at_i>TIMESTAMP&hitsPerPage=10

Example 3: "What has pg posted recently?"

Fetch: https://hn.algolia.com/api/v1/search_by_date?tags=author_pg&hitsPerPage=10

Data Source

Algolia HN Search API — Free, no authentication required. Indexes all public Hacker News content in near real-time.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

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。

平台分布

Codex

34.47%
按下载量换算168

Claude

30.44%
按下载量换算148

Cursor

20.85%
按下载量换算101

Gemini CLI

9.99%
按下载量换算49

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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