sciverse-agent-tools[DEPRECATED] Moved to academic-retrieval (publisher @sciverse). Migrate: openclaw skills install academic-retrieval.
Install via ClawdBot CLI:
clawdbot install sciverse/sciverse-agent-toolsGrade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
eval (Calls external URL not in known-safe list
https://sciverse.spaceAudited Jun 5, 2026 · audit v1.0
Generated Jul 29, 2026
Researchers can use the skill to search and retrieve papers by structured criteria (author, year, journal) for systematic reviews. Example: a team in materials science collects all papers on 'perovskite solar cells' from 2020-2023.
AI-powered assistants can ground answers in recent scientific literature by performing semantic search over paper chunks, then reading relevant sections for citations. Example: a medical chat system explains 'How does CRISPR-Cas9 work?' with excerpt from Nature paper.
Patent attorneys can use structured search to find relevant prior art papers by inventor, journal, or year, and retrieve full text to validate claims. Example: searching for 'transformer' papers by Vaswani et al. to challenge a patent.
Pharma companies can monitor latest research on drug targets by semantic search, extracting key findings from paper chunks to inform pipeline decisions. Example: tracking 'PROTAC' methods for targeted protein degradation.
Educators can compile up-to-date reading lists by searching papers on specific subjects and retrieving abstracts and excerpts. Example: a professor builds a syllabus on 'deep learning for NLP' using recent ACL papers.
Provide limited free access to search and read functions (e.g., 100 queries/month) and charge for higher volume with tiered subscription plans. Revenue from monthly subscriptions and pay-as-you-go credits.
License the skill as a plugin for academic publishers to offer chatbot-based literature exploration on their platforms. Revenue from licensing fees and per-installation charges.
Offer the skill integrated into enterprise knowledge management systems for RAG workflows. Charge a flat annual enterprise fee based on number of users or API calls.
💬 Integration Tip
Set SCIVERSE_API_TOKEN environment variable. For a typical RAG workflow, chain semantic_search -> read_content using doc_id and offset from chunks.
Scored Jun 5, 2026
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