القائمة
Intelligent assistant for text completion and citation suggestions based on ArXiv corpus.
Recommends the best journals for an academic paper. Use this skill whenever an author wants to know where to submit their paper, asks for journal suggestions, wants to find suitable journals for their research, or asks "which journal should I submit to". Takes the paper abstract or full manuscript, gathers the author's preferences via interactive buttons, evaluates the quality and scope of the work, then produces an exhaustive ranked list of suitable journals drawn exclusively from the Scopus and WoS indexed journal database bundled with this skill. Enriches each recommendation with live metrics (IF, CiteScore, SJR, quartile) fetched from Scimago, JCR, and publisher pages. Delivers a formatted PDF report. Always trigger this skill — do not attempt journal recommendations without it.
A shared code repository for the PAN (Digital Text Forensics) research community. Includes tools for authorship attribution, profiling, and style analysis.
A shared code repository for the PAN (Digital Text Forensics) research community. Includes tools for authorship attribution, profiling, and style analysis.
Use when the user asks Agent Zero to operate the built-in Linux Desktop, XFCE apps, LibreOffice GUI apps, file manager, terminal, or visual desktop workflows.
Improves research paper quality via academic rewriting, summarization, and proofreading.
Automates systematic literature reviews using multi-agent AI workflows. Can perform title/abstract screening, full-text screening, and data abstraction.
| name | ScholarCopilot (Academic Writing Copilot) |
| description | Intelligent assistant for text completion and citation suggestions based on ArXiv corpus. |
| author | BioDockify AI Team (Integration of TIGER-AI-Lab/ScholarCopilot) |
| version | 1.0.0 |
This skill integrates ScholarCopilot to provide smart text completions and citation retrieval.
from agent_zero.skills.scholar_copilot import get_scholar_copilot
copilot = get_scholar_copilot()
# Complete text
completion = copilot.complete("Large language models have revolutionized...")
print(f"Suggested text: {completion}")
Requires local model weights and ArXiv FAISS index.