Chinese-first academic Word and PowerPoint workflow for paper reading reports, thesis or group-meeting PPTs, editable DOCX/PPTX generation, Office file inspection, template matching, speaker notes, and layout quality checks. Use when the user asks to read papers into Word reports, create or polish PPT/PPTX, convert paper/thesis materials into slides, edit DOCX/PPTX, inspect Office files, or produce Chinese academic presentation/report deliverables. Preserve English paper titles, formulas, variable names, software commands, and references.
npx skills add https://github.com/zLanqing/codex-claude-academic-skills --skill office-academic-skill
Use this skill for:
.docx and .pptx generation, inspection, repair, and style preservation.Do not use this skill for pure manuscript prose drafting without a Word/PPT deliverable; use research-writing-skill instead. Do not use it for MATLAB, Python analysis, statistics, or plotting unless those outputs are being inserted into Word/PPT.
论文原文, 图表/公式证据, 代码或仿真结果, 根据上下文推断, and 建议.Default output, unless the user asks otherwise:
Before writing, build a source map:
未在原文中明确给出.Use references/report-structure.md for the default report structure and evidence-label format.
For .docx creation or editing:
references/office-docx/ooxml.md, references/office-docx/docx-js.md, and the scripts under references/office-docx/.First clarify only the high-impact missing details:
If the user asks to proceed immediately, make reasonable defaults and state them briefly.
For research PPTs, use a concise structure:
For paper-reading PPTs, use:
10. Relationship to the user's topic.
The academic-pptx repository was reviewed as an external reference. Because it marks its license as proprietary, do not copy its text into outputs or this skill. Use only general academic presentation principles: argument-first structure, action titles, evidence-led slides, and the ghost-deck test.
For template-matched defense PPTs:
Useful bundled resources:
references/thesis-defense-pptx/scripts/ for thesis context extraction, template cloning, slide export, contact sheets, text scans, and overflow inspection.references/office-pptx/ for OOXML-level PPTX inspection and editing.references/office-docx/ for OOXML-level DOCX inspection and editing.Before final delivery, verify what is feasible:
Searches across your Notion workspace, synthesizes findings from multiple pages, and creates comprehensive research documentation saved as new Notion pages. Turns scattered information into structured reports with proper citations and actionable insights.
Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.
Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.
Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.
【强制】所有技术文档查询必须使用本技能,禁止在主对话中直接使用 mcp__context7-mcp 工具。触发关键词:查询/学习/了解某个库或框架的文档、API用法、配置参数、错误解释、版本差异、代码示例、最佳实践。本技能通过 context7-researcher agent 执行查询,避免大量文档内容污染主对话上下文,保持 token 效率。
Generates rich technical documentation pages with dark-mode Mermaid diagrams, source code citations, and first-principles depth. Use when writing documentation, generating wiki pages, creating technical deep-dives, or documenting specific components or systems.
Maximum-saturation research orchestration: ALWAYS proposes the final materials first (PDF+DOCX default), then parallel explore+librarian swarms across codebase, web, official docs, and OSS repos — max-roster teammode when the harness has it — with live journaling, a recursive EXPAND loop driven by leads workers return in message text, empirical verification by running code, and a cited synthesis with charts/Mermaid/assets behind a mandatory visual-QA gate. ACTIVATES ONLY on an explicit user demand for research — the word 'ulw-research' ('/ulw-research', '$ulw-research'), any 'ulw' research wording, 'ultradebate' or 'hyperdebate' research requests, or an explicit request for research / deep research / an ultra-precise investigation, in any language. Never self-activates for ordinary questions, debugging, or implementation context-gathering. While active it overrides exploration-bounding defaults: exhaustive coverage is the goal.
"Solve competition math problems (IMO, Putnam, USAMO, AIME) with adversarial verification that catches the errors self-verification misses. Activates when asked to 'solve this IMO problem', 'prove this olympiad inequality', 'verify this competition proof', 'find a counterexample', 'is this proof correct', or for any problem with 'IMO', 'Putnam', 'USAMO', 'olympiad', or 'competition math' in it. Uses pure reasoning (no tools) — then a fresh-context adversarial verifier attacks the proof using specific failure patterns, not generic 'check logic'. Outputs calibrated confidence — will say 'no confident solution' rather than bluff. If LaTeX is available, produces a clean PDF after verification passes."
Take zlanqing/office-academic-skill from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.