name: 4d-compression-core version: 1.0.2 description: "把长内容压缩成结构化向量——节省 60-80% Token,保留核心信息" metadata: { "openclaw": { "emoji": "🌀", "requires": { "bins": ["jq", "awk"] }, "triggers": ["压缩", "4d",...
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Search academic papers and conduct literature reviews using OpenAlex API (free, no key needed). Use when the user needs to find scholarly papers by topic/author/DOI, explore citation chains, get structured paper metadata (title, authors, abstract, citations, DOI, open access URL), fetch full text of open access papers, or conduct automated literature reviews with theme identification and synthesis. Triggers on requests involving academic search, paper lookup, citation analysis, literature review, research synthesis, or scholarly reference gathering.
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安装前可以查看交给 AI 代理的指令内容。
Search 250M+ academic works via OpenAlex. No API key required.
Built by Topanga — AI Research Consultant
python3 scripts/scholar-search.py search "transformer architectures" --limit 10
python3 scripts/scholar-search.py author "Yann LeCun" --limit 5
python3 scripts/scholar-search.py doi "10.1038/s41586-021-03819-2"
python3 scripts/scholar-search.py citations "10.1038/s41586-021-03819-2" --direction both
python3 scripts/scholar-search.py deep "10.1038/s41586-021-03819-2"
python3 scripts/scholar-search.py search "CRISPR" --json
Automated multi-step literature review:
python3 scripts/literature-review.py "algorithmic literacy in education" --papers 30 --output review.md
This will:
Options:
--papers N — Target number of papers (default: 20)--output FILE — Write review to file (default: stdout)--years 2020-2025 — Restrict publication year range--json — Output structured JSON instead of markdownAll search commands return structured data per paper:
--sort citations for most-citedsearch + deep for quick triage: search first, deep-read promising hits/tmp/litreview_cache/ to avoid re-fetching还没有评价。欢迎分享你的使用感受。
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name: 4d-compression-core version: 1.0.2 description: "把长内容压缩成结构化向量——节省 60-80% Token,保留核心信息" metadata: { "openclaw": { "emoji": "🌀", "requires": { "bins": ["jq", "awk"] }, "triggers": ["压缩", "4d",...
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Use cheap, TEE-verified AI models from the 0G Compute Network as OpenClaw providers. Discover available models and compare pricing vs OpenRouter, verify provider integrity via hardware attestation (Intel TDX), manage your 0G wallet and sub-accounts, and configure models in OpenClaw with one workflow. Supports DeepSeek, GLM-5, Qwen, and other models available on the 0G marketplace.
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Send and receive P2P messages using disposable numbers and PINs. No servers, no accounts. Use for human notifications, approval flows, and agent-to-agent communication.
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Query historical crypto market data from 0xArchive across Hyperliquid, Lighter.xyz, and HIP-3. Covers orderbooks, trades, candles, funding rates, open interest, liquidations, and data quality. Use when the user asks about crypto market data, orderbooks, trades, funding rates, or historical prices on Hyperliquid, Lighter.xyz, or HIP-3.
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Find and complete paid tasks on the 0xWork decentralized marketplace (Base chain, USDC escrow). Use when: the agent wants to earn money/USDC by doing work, discover available tasks, claim a bounty, submit deliverables, check earnings or wallet balance, or set up as a 0xWork worker. Task categories: Writing, Research, Social, Creative, Code, Data. NOT for: posting tasks (use the website), managing the 0xWork platform, or frontend development.
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Patterns and practices that dramatically accelerate development velocity. Covers parallel execution, automation, feedback loops, workflow optimization, and anti-pattern avoidance. Use when starting projects, planning sprints, optimizing workflows, or onboarding developers.
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