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kagi-enrich卡吉丰富

Agent Skill

kagi-enrich 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

18,010

周安装

758

GitHub Stars

公开资料未说明

下载量

6,307
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:kagi-enrich(卡吉丰富)
来源仓库:https://github.com/joelazar/kagi-enrich
安装命令:
openclaw skills install kagi-enrich
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 kagi-enrich

简介

基于 Kagi 搜索引擎增强非主流内容检索能力。

  • 适合查找无广告、独立原创的网络资讯资源。
  • 利用 Teclis 和 TinyGem 索引扩展常规搜索结果。
  • 需拥有 Kagi 高级订阅账号方可启用此技能。
  • 建议明确关键词以提高定向检索效率。kagi-enrich 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
kagi-enrich
description
Search Kagi's unique non-commercial web (Teclis) and non-mainstream news (TinyGem) indexes for independent, ad-free content you won't find in regular search results. Use when you want to discover small-web sites, independent blogs, niche discussions, or non-mainstream news on a topic.

Kagi Enrichment

Search Kagi's proprietary enrichment indexes using the Kagi Enrichment API. These are Kagi's "secret sauce" — curated indexes of non-commercial and independent content that complement mainstream search results.

Two indexes are available:

IndexBackendBest for
webTeclisIndependent websites, personal blogs, open-source projects, non-commercial content
newsTinyGemNon-mainstream news sources, interesting discussions, off-the-beaten-path journalism

This skill uses a Go binary for fast startup and zero runtime dependencies. The binary can be downloaded pre-built or compiled from source.

Setup

Requires a Kagi account with API access enabled. Uses the same KAGI_API_KEY as all other kagi-* skills.

  1. Create an account at https://kagi.com/signup
  2. Navigate to Settings → Advanced → API portal: https://kagi.com/settings/api
  3. Generate an API Token
  4. Add funds at: https://kagi.com/settings/billing_api
  5. Add to your shell profile (~/.profile or ~/.zprofile):
   export KAGI_API_KEY="your-api-key-here"
  1. Install the binary — see Installation below

Pricing

$2 per 1,000 searches ($0.002 per query). Billed only when non-zero results are returned.

Usage

# Search the independent web (Teclis index) — default
{baseDir}/kagi-enrich.sh web "rust async programming"
{baseDir}/kagi-enrich.sh "rust async programming"        # web is the default

# Search non-mainstream news (TinyGem index)
{baseDir}/kagi-enrich.sh news "open source AI"

# Limit number of results
{baseDir}/kagi-enrich.sh web "sqlite internals" -n 5

# JSON output
{baseDir}/kagi-enrich.sh web "zig programming language" --json
{baseDir}/kagi-enrich.sh news "climate change solutions" --json

# Custom timeout
{baseDir}/kagi-enrich.sh web "query" --timeout 30

Options

FlagDescription
-n <num>Max results to display (default: all returned)
--jsonEmit JSON output
--timeout <sec>HTTP timeout in seconds (default: 15)

Output

Default (text)

--- Result 1 ---
Title: SQLite Internals: How The World's Most Used Database Works
URL:   https://www.compileralchemy.com/books/sqlite-internals/
Date:  2023-04-01T00:00:00Z
       A deep-dive into how SQLite's B-tree storage engine, WAL journal...

--- Result 2 ---
...

[API Balance: $9.9980 | results: 15]

JSON (--json)

{
  "query": "sqlite internals",
  "index": "web",
  "meta": {
    "id": "abc123",
    "node": "us-east4",
    "ms": 386,
    "api_balance": 9.998
  },
  "results": [
    {
      "rank": 1,
      "title": "SQLite Internals: How The World's Most Used Database Works",
      "url": "https://www.compileralchemy.com/books/sqlite-internals/",
      "snippet": "A deep-dive into SQLite's B-tree...",
      "published": "2023-04-01T00:00:00Z"
    }
  ]
}

When to Use

  • Use web when you want independent, non-commercial perspectives on a topic — personal blogs, indie projects, academic pages, niche communities — results that mainstream search drowns out with SEO-optimized commercial sites
  • Use news when you want news and discussions from sources outside the mainstream media cycle — niche outlets, Hacker News threads, Reddit discussions, independent journalists
  • Combine with kagi-search for the most complete picture: kagi-search for high-quality general results, kagi-enrich web for independent voices, kagi-enrich news for alternative news angles
  • Use kagi-fastgpt instead when you need a synthesized answer rather than a list of sources

Note on result counts

The enrichment indexes are intentionally niche — they may return fewer results than general search. No results for a query means no relevant content was found in that index (and you won't be billed).

Installation

Option A — Download pre-built binary (no Go required)

OS=$(uname -s | tr '[:upper:]' '[:lower:]')
ARCH=$(uname -m)
case "$ARCH" in
  x86_64)        ARCH="amd64" ;;
  aarch64|arm64) ARCH="arm64" ;;
esac

TAG=$(curl -fsSL "https://api.github.com/repos/joelazar/kagi-skills/releases/latest" | grep '"tag_name"' | cut -d'"' -f4)
BINARY="kagi-enrich_${TAG}_${OS}_${ARCH}"

mkdir -p {baseDir}/.bin
curl -fsSL "https://github.com/joelazar/kagi-skills/releases/download/${TAG}/${BINARY}" \
  -o {baseDir}/.bin/kagi-enrich
chmod +x {baseDir}/.bin/kagi-enrich

# Verify checksum (recommended)
curl -fsSL "https://github.com/joelazar/kagi-skills/releases/download/${TAG}/checksums.txt" | \
  grep "${BINARY}" | sha256sum --check

Pre-built binaries are available for Linux and macOS (amd64 + arm64) and Windows (amd64).

Option B — Build from source (requires Go 1.26+)

cd {baseDir} && go build -o .bin/kagi-enrich .

Alternatively, just run {baseDir}/kagi-enrich.sh directly — the wrapper auto-builds on first run if Go is available.

The binary has no external dependencies — only the Go standard library.

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

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

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。

平台分布

OpenClaw

94.09%
按下载量换算5,934

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

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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