Alternatives

Graph Adversarial Learning Literature alternatives for AI agents.

Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.

Current skill

Graph Adversarial Learning Literature

A curated list of adversarial attacks and defenses papers on graph-structured data.

51
Quality
72
Trust
864
Stars
#1

Academic Research Skills

Similarity 111Trust 87Excellent 100

Academic Research Skills for Claude Code: research → write → review → revise → finalize

38K starsJul 18, 2026 pushresearchPythonResearch
$ npx skills add Imbad0202/academic-research-skills
#2

Academic Research Skills Codex

Similarity 105Trust 82Excellent 95

Codex-native Academic Research Skills suite for human-in-the-loop academic research workflows

3.8K starsJun 14, 2026 pushresearchPythonResearch
$ npx skills add Imbad0202/academic-research-skills-codex
#3

Local Deep Research

Similarity 100Trust 89Excellent 99

~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted.

8.7K starsJul 18, 2026 pushresearchPythonResearch
$ npx skills add LearningCircuit/local-deep-research
#4

ChatPaper

Similarity 99Trust 84Excellent 91

Use ChatGPT to summarize the arXiv papers. 全流程加速科研,利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复

20K starsMar 2, 2026 pushresearchPythonResearch
$ npx skills add kaixindelele/ChatPaper
#5

GPT Researcher

Similarity 96Trust 85Excellent 100

Run autonomous deep research over web and local sources

30K starsAug 27, 2026 pushresearchPythonResearch Agent
$ npx skills add assafelovic/gpt-researcher
#6

nature-writing

Similarity 95Trust 80Excellent 100

Draft, restructure, or plan Nature-style manuscript sections and initial-submission materials from author-provided claims, results, figures, notes, or Chinese drafts. Use for abstracts, introductions, related work, methods, Results or experiments, discussions, conclusions, titles, full manuscript arguments, and first-submission packages such as cover letters, title pages, highlights, author contributions, availability or declaration text, and reviewer suggestions. Also use to classify Results evidence, decide what belongs in main text, captions, Methods or source data, or Supplementary Information, compress Results to the shortest sufficient evidence chain, prevent revision accretion, and audit paragraph necessity or claim repetition. Trigger on drafting a paper or section, structuring a manuscript, academic writing, first submission, 投稿材料、首次投稿、投稿信、标题页、亮点、作者贡献、数据可用性声明、推荐审稿人.

39K starsSep 2, 2026 pushresearchClaude Code
$ npx skills add Yuan1z0825/nature-skills --skill nature-writing
#7

DeepResearch

Similarity 95Trust 85Excellent 97

Tongyi Deep Research, the Leading Open-source Deep Research Agent

20K starsFeb 27, 2026 pushresearchPythonResearch Agent
$ npx skills add Alibaba-NLP/DeepResearch
#8

Last30days Skill

Similarity 89Trust 92Excellent 100

Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.

64K starsOct 7, 2026 pushresearchPythonClaude Code
$ npx skills add mvanhorn/last30days-skill -g
#9

mono-color

Similarity 83Trust 81Excellent 100

Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.

1.9K starsSep 1, 2026 pushresearchClaude Code
$ npx skills add yanliudesign/mono-color-skill --skill mono-color
#10

Qlib

Similarity 77Trust 89Excellent 100

Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.

44K starsApr 22, 2026 pushfinancePythonFinance
$ npx skills add microsoft/qlib
#11

RD Agent

Similarity 75Trust 89Excellent 100

Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. 🔗https://aka.ms/RD-Agent-Tech-Report

13K starsJun 15, 2026 pushautomationPythonAutomation
$ npx skills add microsoft/RD-Agent
#12

Pyod

Similarity 74Trust 88Excellent 99

A Python library for anomaly detection across tabular, time series, graph, text, and image data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.

9.9K starsJun 5, 2026 pushml-automationPythonMachine Learning
$ npx skills add yzhao062/pyod
#13

Awesome Openclaw Skills

Similarity 69Trust 92Excellent 100

The awesome collection of OpenClaw skills. 5,400+ skills filtered and categorized from the official OpenClaw Skills Registry.🦞

53K starsSep 21, 2026 pushagent-skillsAI AgentsClaude Code
$ npx skills add VoltAgent/awesome-openclaw-skills
#14

Transformers

Similarity 69Trust 89Excellent 100

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

162K starsJun 16, 2026 pushml-automationPythonMachine Learning
$ npx skills add huggingface/transformers
#15

Daily Stock Analysis

Similarity 69Trust 89Excellent 100

LLM驱动的 A/H/美股智能分析:多数据源行情 + 实时新闻 + LLM决策仪表盘 + 多渠道推送,零成本定时运行,纯白嫖. LLM-powered stock analysis system for A/H/US markets.

52K starsJun 29, 2026 pushfinancePythonFinance
$ npx skills add ZhuLinsen/daily_stock_analysis
#16

Gradio

Similarity 69Trust 89Excellent 100

Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

43K starsJun 17, 2026 pushdata-analysisPythonData Analysis
$ npx skills add gradio-app/gradio

How to choose

When should you switch?

Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep Graph Adversarial Learning Literature if it already passes your workflow test and repository review.

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