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ResearchzLanqing/codex-claude-academic-skills

Three Chinese-first research skills that run on both Claude Code and Codex

Our takeThe part worth copying is that academic integrity is written as instructions: no fabricated data, DOIs or journals, and every piece of content is classified as quotation, confirmed fact, reasonable inference or writing suggestion, so the author can see at a glance which sentences have a source. The real danger in academic writing is not weak prose but a model writing inference as though it were established fact, and that four-way split blocks exactly that. The three skills also compose: figures, then body text, then defence slides.

4,117 stars, MIT. research-writing handles drafting, revising and polishing paper sections plus rebuttals; office-academic generates and edits academic Word and PPT at the OOXML layer (literature reports, group meetings, proposals, defences); scientific-toolkit covers MATLAB/Python simulation, signal processing, statistics, machine learning and paper figures, with literature search across arXiv, PubMed, CrossRef, Semantic Scholar and OpenAlex.

Claude CodeCodex
git clone https://github.com/zLanqing/codex-claude-academic-skills && cp -r codex-claude-academic-skills/research-writing-skill ~/.claude/skills/
PythonzLanqing4.1k
Three Chinese-first research skills that run on both Claude Code and Codex
Research199-biotechnologies/claude-deep-research-skill

An eight-phase deep research pipeline with an evidence ledger

Our takeThe soul is four append-only JSONL ledgers: sources, evidence, claims and run_manifest. Every factual claim must carry an inline [N] backed by evidence.jsonl, unsupported claims may not ship, and validate_report.py plus verify_citations.py check the result. The repo has no LICENSE file, which under default copyright means all rights reserved: you can read and run it locally, but get the author's permission before redistributing or using it commercially.

1,051 stars. Four intensity modes — Quick at 3 phases and 2-5 minutes, Standard at 6, Deep at 8, UltraDeep at 8+ and 20-45 minutes — running SCOPE, PLAN, RETRIEVE, TRIANGULATE, outline refinement, SYNTHESIZE, CRITIQUE, REFINE and PACKAGE, and emitting Markdown, a McKinsey-style HTML report and a PDF.

Claude Code
git clone https://github.com/199-biotechnologies/claude-deep-research-skill ~/.claude/skills/deep-research
Python199-biotechnologies1.1k
An eight-phase deep research pipeline with an evidence ledger