Skip to main content
在 Manus 中运行任何 Skill
一键导入
GitHub 仓库

ai4s-skills

ai4s-skills 收录了来自 ai4s-research 的 7 个 skills,并提供仓库级职业覆盖和站内 skill 详情页。

已收集 skills
7
Stars
144
更新
2026-07-06
Forks
10
职业覆盖
5 个职业分类 · 已分类 100%
仓库浏览

这个仓库中的 skills

mindmap-render
软件开发工程师

Generate beautiful, high-resolution mindmaps from Markdown unordered lists. Outputs interactive HTML, HD PNG, and PDF with colorful branch themes.

2026-07-06
integrity-auditor
其他高等院校教师

Use when the user wants a paper audited for integrity issues — image misuse, numerical anomalies, logical gaps — and needs a reviewable evidence report. Works on external papers (PDF / DOI / arXiv) and on outputs from a local paper-writer run. Single-stage skill.

2026-07-03
experiment-suite
数据科学家

Use when the user has a research question and needs a complete experiment package — design document, runnable code, results (measured or simulated with honest provenance), publication-grade figures, structured report. Single-stage, no Python runtime.

2026-07-01
ai4s-agent
软件开发工程师

Use when the user wants an end-to-end AI4S research pipeline — broad direction or specific topic in, full research package out (exploration + literature survey + experiment + paper). Meta-skill that chains the four downstream skills in order. Pure markdown, no Python runtime.

2026-06-28
literature-survey
其他高等院校教师

Use when the user wants a comprehensive literature survey on a specific research topic. Outputs a complete PDF survey (6–20 pages, 60+ real citations, 100+ recommended) with LaTeX source, taxonomy figures, and a classified literature table. Single-stage, no Python runtime.

2026-06-28
paper-writer
技术写作员

Use when the user wants a complete, publication-grade research paper on a specific topic — produces 200+ real citations, 4–8 publication-grade figures, and 7 sections of substantive prose compiled to PDF in one pass. No skeleton stage.

2026-06-28
research-explorer
市场调研分析师与营销专员

Use when the user has a vague research direction and wants to explore feasible specific topics. Outputs a structured analysis with candidate topics, innovation/feasibility scoring, and a pre-survey of 20–30 representative works. Single-stage, no Python runtime.

2026-06-28