ScienceClaw is an agent system for scientific work that completes tasks as typed, executable workflows and turns replay-verified improvements into reusable skills and operators. It is intended for AI-assisted research across natural and social science disciplines. The catalogue entries are its skills and instruction for use with the system.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add beita6969/ScienceClaw --skill multi-search-enginegit clone --depth 1 https://github.com/beita6969/ScienceClawWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/beita6969/scienceclaw/multi-search-engine)<a href="https://agentmods.dev/skills/beita6969/scienceclaw/multi-search-engine"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/multi-search-engine/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/beita6969/scienceclaw/multi-search-engine"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/multi-search-engine.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00046 | $0.00988 |
| Opus 5.5 | $0.00018 | $0.00395 |
| Sonnet 5.5 | $0.00009 | $0.00198 |
| Haiku 4.5 | $0.00005 | $0.00099 |
Grade A, and why
multi-search-engine scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
4 near-identical copies found in the catalogue:
- multi-search-engine — 100% identical, 0 lines differ
- multi-search-engine — 100% identical, 0 lines differ
- multi-search-engine — 100% identical, 0 lines differ
- multi-search-engine — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi Search Engine v2.0.1
Integration of 17 search engines for web crawling without API keys.
Search Engines
Domestic (8)
- Baidu:
https://www.baidu.com/s?wd={keyword} - Bing CN:
https://cn.bing.com/search?q={keyword}&ensearch=0 - Bing INT:
https://cn.bing.com/search?q={keyword}&ensearch=1 - 360:
https://www.so.com/s?q={keyword} - Sogou:
https://sogou.com/web?query={keyword} - WeChat:
https://wx.sogou.com/weixin?type=2&query={keyword} - Toutiao:
https://so.toutiao.com/search?keyword={keyword} - Jisilu:
https://www.jisilu.cn/explore/?keyword={keyword}
International (9)
- Google:
https://www.google.com/search?q={keyword} - Google HK:
https://www.google.com.hk/search?q={keyword} - DuckDuckGo:
https://duckduckgo.com/html/?q={keyword} - Yahoo:
https://search.yahoo.com/search?p={keyword} - Startpage:
https://www.startpage.com/sp/search?query={keyword} - Brave:
https://search.brave.com/search?q={keyword} - Ecosia:
https://www.ecosia.org/search?q={keyword} - Qwant:
https://www.qwant.com/?q={keyword} - WolframAlpha:
https://www.wolframalpha.com/input?i={keyword}
Quick Examples
// 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"})
Advanced Operators
| 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 |
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 111 lines · 46 tokens per session scan A ef2d2706e82a
multi-search-engine is a skill published in the GitHub repository beita6969/ScienceClaw (1,019 stars, last pushed 10d ago), licensed MIT. It adds 46 tokens to every session and 988 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
biopython
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use…
scanpy
Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use…
structure-prediction
Protein structure prediction from sequence. ESMFold-based, single GPU, no MSA needed. Predicts 3D structures with pLDDT confidence scores for drug discovery targets.
biomcp
Search and retrieve biomedical data - genes, variants, clinical trials, diagnostic tests, articles, drugs, diseases, pathways, proteins, adverse events, pharmacogenomics, and phenotype-disease matching. Use for gene function, variant pathogenicity, trials, diagnostics, drug safety, pathway context, disease workups…
biomcp-research
Do biomedical literature and variant research with the BioMCP CLI, and file what you learn about the tool itself as issues in the biomcp repo.
biological-expert
Expert-level biology, biotechnology, genetics, bioinformatics, and computational biology. Use when the user mentions biology, biotechnology, genetics, bioinformatics, or genomics, or when the task involves Molecular Biology, Genomics & Bioinformatics, Systems Biology, or Data Analysis.