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Multi search engine integration with 17 engines (8 CN + 9 Global). Supports advanced search operators, time filters, site search, privacy engines, and WolframAlpha knowledge queries. No API keys required.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Use this model doc whenever the user wants to run BrainGNN for fMRI phenotype prediction, including graph construction, training, and evaluation. This document focuses on model-level usage and delegates upstream preprocessing to fmri-skill (and optionally hcpya-skill for HCP data).
Use this skill when users need to build, populate, or extend a domain-specific knowledge graph from literature and structured databases. Triggers include: 'build knowledge graph', 'extract claims from papers', 'ingest data into graph', 'batch extract claims', 'knowledge graph construction', 'populate graph from PubMed', 'extract structured claims', 'ingest atlas data', or any request involving knowledge graph population from scientific literature or biomedical databases. Covers both structured data ingestion (Phase 1) and LLM-based claim extraction from papers (Phase 2).
Use this skill whenever the user wants to formalize a network architecture and derive theoretical components from a research idea. Triggers include: 'method design', 'design method', 'network architecture', 'formula derivation', 'method-design', 'theoretical framework', 'derive equations', 'compare alternatives', 'architecture tournament', 'rank designs', 'design space exploration', or any request to transform IDEA.md into a detailed METHOD.md. This skill is the **mandatory interface-layer method formalizer** in NeuroClaw: it reads IDEA.md, optionally drafts N alternative architectures and ranks them via a Bradley-Terry pairwise tournament (Tournament Mode), designs concrete network structures (layers, modules, connections), performs mathematical derivations (equations, loss functions, proofs), and always outputs a structured METHOD.md.
Use this skill whenever the user wants to remove site/scanner/batch effects from neuroimaging features before running downstream models, run mega-analysis across multiple datasets, or evaluate models with leave-site-out / site-stratified protocols. Triggers include: 'harmonize', 'ComBat', 'CovBat', 'site effect', 'scanner effect', 'batch effect', 'leave-site-out', 'mega-analysis', 'multi-site', 'cross-site', 'neuroHarmonize'. This is a horizontal cross-cutting layer between dataset skills and model skills.
Use this skill whenever the user wants to run phenotype-prediction models, browse model cards, map model inputs/outputs, or choose an execution route for fMRI/sMRI based models. This is a model-entry orchestration skill: it routes requests to model-specific docs and delegates preprocessing to modality skills.
Use this model doc whenever the user wants to run Com-BrainTF (Community-aware Brain Transformer) for fMRI phenotype prediction. Com-BrainTF uses dense FC matrices with a two-level Transformer (per-community local + global) and DEC pooling. NeuroClaw auto-derives community partitions from atlas naming conventions (Yeo 7-net for Schaefer, lobe-based for AAL).
| name | multi-search-engine |
| description | Multi search engine integration with 17 engines (8 CN + 9 Global). Supports advanced search operators, time filters, site search, privacy engines, and WolframAlpha knowledge queries. No API keys required. |
| layer | base |
| skill_type | tool |
| dependencies | [] |
Integration of 17 search engines for web crawling without API keys.
https://www.baidu.com/s?wd={keyword}https://cn.bing.com/search?q={keyword}&ensearch=0https://cn.bing.com/search?q={keyword}&ensearch=1https://www.so.com/s?q={keyword}https://sogou.com/web?query={keyword}https://wx.sogou.com/weixin?type=2&query={keyword}https://so.toutiao.com/search?keyword={keyword}https://www.jisilu.cn/explore/?keyword={keyword}https://www.google.com/search?q={keyword}https://www.google.com.hk/search?q={keyword}https://duckduckgo.com/html/?q={keyword}https://search.yahoo.com/search?p={keyword}https://www.startpage.com/sp/search?query={keyword}https://search.brave.com/search?q={keyword}https://www.ecosia.org/search?q={keyword}https://www.qwant.com/?q={keyword}https://www.wolframalpha.com/input?i={keyword}// Basic search
web_fetch({"url": "https://www.google.com/search?q=python+tutorial"})
// Site-specific
web_fetch({"url": "https://www.google.com/search?q=site:github.com+react"})
// File type
web_fetch({"url": "https://www.google.com/search?q=machine+learning+filetype:pdf"})
// Time filter (past week)
web_fetch({"url": "https://www.google.com/search?q=ai+news&tbs=qdr:w"})
// Privacy search
web_fetch({"url": "https://duckduckgo.com/html/?q=privacy+tools"})
// DuckDuckGo Bangs
web_fetch({"url": "https://duckduckgo.com/html/?q=!gh+tensorflow"})
// Knowledge calculation
web_fetch({"url": "https://www.wolframalpha.com/input?i=100+USD+to+CNY"})
| Operator | Example | Description |
|---|---|---|
site: | site:github.com python | Search within site |
filetype: | filetype:pdf report | Specific file type |
"" | "machine learning" | Exact match |
- | python -snake | Exclude term |
OR | cat OR dog | Either term |
| Parameter | Description |
|---|---|
tbs=qdr:h | Past hour |
tbs=qdr:d | Past day |
tbs=qdr:w | Past week |
tbs=qdr:m | Past month |
tbs=qdr:y | Past year |
| Bang | Destination |
|---|---|
!g | |
!gh | GitHub |
!so | Stack Overflow |
!w | Wikipedia |
!yt | YouTube |
integrate x^2 dx100 USD to CNYAAPL stockweather in Beijingreferences/advanced-search.md - Domestic search guidereferences/international-search.md - International search guideCHANGELOG.md - Version historyMIT
academic-research-hub → scholarly paper searchCore multi-engine search integration for NeuroClaw (v2.0.1).
Used as the primary literature & web search backend across all interface-layer skills.
Created At: 2026-03-24 00:00 HKT
Last Updated At: 2026-03-26 00:18 HKT
Author: chengwang96