UnaryLab
Official@unarylab · United States of America
A group of people at UCF ECE who work on emerging computer architecture and systems
Agent Skills by UnaryLab
Showing 12 vetted skills indexed across 1 GitHub repositories.
UnaryLabidea-evaluate
Evaluate research ideas for long-term impact using an IEEE Micro Top Picks lens.
UnaryLabpaper-draft
Draft venue-aware academic prose from research fragments with claim-first structure.
UnaryLabchalk-talk
Convert a research concept into a chalkboard diagram with narration and alt text.
UnaryLabresult-generate
Convert experimental outputs into publication-quality figures and tables with statistics.
UnaryLabpaper-polish
Diagnose and fix academic paper issues with prioritized diff-comment feedback.
UnaryLabidea-brainstorm
Generate research ideas sorted into T1–T5 novelty tiers with prior-work verification.
UnaryLabcode-clean
Refactor research codebases with behavior-preserving, risk-tiered cleanup.
UnaryLabpaper-read
Analyzes PDFs or arXiv links applying Wes's three-pass reading method with structured outputs.
UnaryLabcode-implement
Reproduce external research code results with hermetic environments and reproduction logs.
UnaryLabexperiment-scaffold
Scaffold an approval-gated experimental framework with baselines and walking-skeleton validation.
UnaryLabartifact-create
Package research code into a Docker artifact with pinned dependencies and clean-room verification.
UnaryLabliterature-survey
Search academic indexes and generate a cited Markdown literature survey.
Frequently Asked Questions About UnaryLab
FAQPage SchemaWhat specific research tasks does UnaryLab support?▼
UnaryLab supports the full research lifecycle, including evaluating novelty tiers for new concepts, drafting venue-aware academic prose, refactoring research codebases, and packaging experimental results into verified, containerized artifacts. It also facilitates systematic literature surveys and the conversion of research concepts into structured chalkboard diagrams.
Who is the target audience for these research capabilities?▼
The primary target audience includes academic researchers, computer architecture students, and engineering faculty at institutions like UCF ECE. It is designed for scholars who require rigorous, peer-review-ready documentation, reproducible experimental frameworks, and structured methods for managing complex academic literature and research codebases.
What are the prerequisites for using these research support capabilities?▼
Users require access to research fragments, experimental outputs, or existing codebases to leverage these capabilities. For artifact creation, a basic understanding of containerization is beneficial, while literature surveys require valid arXiv links or PDF documents to initiate the structured three-pass reading and analysis process.