richard-kim-79

richard-kim-79 / archora-skills

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Academic research agent skills for Claude Code and other Agent Skills-compatible tools. Hypothesis generation, experiment design, paper drafting, peer review simulation, and more.

academic agent-skills claude hypothesis peer-review
36
9
80% credibility
Found May 17, 2026 at 36 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

Archora Skills is a collection of AI research assistant abilities designed for academics and researchers. It provides nine specialized skills that work with AI coding assistants: generating research hypotheses from your notes, designing experiments to test those hypotheses, writing structured academic papers, creating data visualizations, checking for statistical errors, generating counterarguments, simulating journal peer review, surfacing themes across your research, and organizing notes into a wiki. The tool chains these skills together into a complete research pipeline, from raw notes to a polished, peer-reviewed paper draft.

How It Works

1
🔬 You discover a research assistant

You hear about a tool that can help you write academic papers, check your statistics, and even simulate peer review.

2
📦 You install the research skills

You add these research abilities to your AI assistant with a simple command, and everything sets itself up automatically.

3
✨ Your research comes together

You ask your assistant to organize your notes, generate research questions, design experiments, and write your paper draft—all in one flowing conversation.

4
📊 You create figures and check your work

The assistant generates charts and visualizations for your data, then carefully checks your statistics for any errors.

5
You choose how to finish
👥
Simulate peer review

Get feedback as if multiple expert reviewers read your paper

🎭
Generate counterarguments

Have an AI play devil's advocate and challenge your assumptions

🎓 Your paper is ready

You've completed a full academic paper with hypotheses, experiments, figures, and critical review—all with intelligent assistance along the way.

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AI-Generated Review

What is archora-skills?

archora-skills is a collection of AI agent prompts designed to automate academic research workflows. It targets Claude Code and other Agent Skills-compatible tools, letting you chain together tasks like hypothesis generation, experimental validation, paper drafting, and peer review simulation. The skills work on your local Markdown files and research notes, orchestrating a full pipeline from raw ideas to submission-ready drafts. Installation is a single command: npx skills add with the GitHub URL.

Why is it gaining traction?

The workflow diagram is the hook: raw notes transform into hypotheses, experiments, figures, and a structured paper through a logical chain. Researchers have long struggled with the tedious parts of academic work, and this offers a scriptable assistant for those mechanical tasks. The peer review simulation and counterargument skills specifically target the pre-submission stress-testing that usually requires colleagues or actual reviewers.

Who should use this?

Graduate students drowning in literature reviews and note organization will find the wiki-sync and synthesis skills immediately useful. Early-career researchers who want a second opinion before submission could use the peer-review simulation as a sanity check. Established labs looking to standardize research documentation might adopt this as part of their workflow, though the CLI-first approach assumes some technical comfort.

Verdict

This is a promising concept with a low credibility score of 0.800000011920929% and only 36 stars, signaling an early-stage, single-maintainer project. The workflow design is thoughtful and the installation is trivial, but the lack of community validation and minimal documentation warrant caution for production use. Try it on a low-stakes project to evaluate fit, but do not depend on it for time-sensitive research deadlines without thorough testing first.

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