·search-layer
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search-layer

Multi-source search and deduplication layer with intent-aware scoring. Integrates Brave Search (web_search), Exa, Tavily, and Grok to provide high-coverage, high-quality results. Automatically classifies query intent and adjusts search strategy, scoring weights, and result synthesis accordingly. Triggers on "deep search", "multi-source search", or when high-quality research is needed.

13Installs·0Trend·@blessonism

Installation

$npx skills add https://github.com/blessonism/openclaw-skills --skill search-layer

How to Install search-layer

Quickly install search-layer AI skill to your development environment via command line

  1. Open Terminal: Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.)
  2. Run Installation Command: Copy and run this command: npx skills add https://github.com/blessonism/openclaw-skills --skill search-layer
  3. Verify Installation: Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw

Source: blessonism/openclaw-skills.

SKILL.md

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| 意图 | 识别信号 | Mode | Freshness | 权重偏向 |

| Factual | "什么是 X"、"X 的定义"、"What is X" | answer | — | 权威 0.5 | | Status | "X 最新进展"、"X 现状"、"latest X" | deep | pw/pm | 新鲜度 0.5 | | Comparison | "X vs Y"、"X 和 Y 区别" | deep | py | 关键词 0.4 + 权威 0.4 | | Tutorial | "怎么做 X"、"X 教程"、"how to X" | answer | py | 权威 0.5 | | Exploratory | "深入了解 X"、"X 生态"、"about X" | deep | — | 权威 0.5 |

| News | "X 新闻"、"本周 X"、"X this week" | deep | pd/pw | 新鲜度 0.6 | | Resource | "X 官网"、"X GitHub"、"X 文档" | fast | — | 关键词 0.5 |

Facts (cite-ready)

Stable fields and commands for AI/search citations.

Install command
npx skills add https://github.com/blessonism/openclaw-skills --skill search-layer
Category
</>Dev Tools
Verified
First Seen
2026-02-22
Updated
2026-03-11

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Quick answers

What is search-layer?

Multi-source search and deduplication layer with intent-aware scoring. Integrates Brave Search (web_search), Exa, Tavily, and Grok to provide high-coverage, high-quality results. Automatically classifies query intent and adjusts search strategy, scoring weights, and result synthesis accordingly. Triggers on "deep search", "multi-source search", or when high-quality research is needed. Source: blessonism/openclaw-skills.

How do I install search-layer?

Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/blessonism/openclaw-skills --skill search-layer Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw

Where is the source repository?

https://github.com/blessonism/openclaw-skills