rigorous: A comprehensive suite of tools, built to liberate science by making the creation, evaluation

by Agentic-Systems-Lab · Agent Tool · ★ 254

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 63/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

academic-paperacademic-writingai-agentsai-toolsllmmanuscript-analysespythonresearchscience

Quick Facts

Stars254
Forks20
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score63/100
Open Issues3
Last Updated2025-08-08
Created2025-04-09
Platformspython
Est. Tokens~12k

About rigorous

Rigorous AI-Powered Scientific Manuscript Analysis v0.2 Now Live: The latest version of the AI Reviewer (v0.2) is now available at https://www.rigorous.review/. Upload your manuscript, provide context on your target journal and receive structured feedback directly online via an interactive interface — now with progress tracking built in.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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