Turn a vague research approach into a concrete method proposal with focused contributions and minimal validation experiments. Ground the plan in relevant papers, then refine it through GPT-6-Astra reviews while preserving the original problem and resource constraints.
Turn ARIS research reports in Markdown or JSON into a single HTML file for reading. Choose a report or dashboard layout, retain source version details, and optionally review whether the conversion preserves content and structure.
Find published journal and conference papers through Semantic Scholar, filtering by year, field, type, or citation count. Compare publication details and abstracts, with DOI links, short summaries, and open access PDFs when available.
Check mathematical proofs in LaTeX with review by a separate AI model. Identify missing assumptions and unsupported steps, explore counterexamples, repair derivations, and keep an audit record of issues, changes, and follow-up reviews.
Search patent databases and academic literature for earlier disclosures related to an invention. The workflow extracts technical features, compares overlapping approaches, and produces a report on relevant references, potential patent coverage, and areas where novelty may be strongest.
Improve research through repeated Gemini reviews, code changes, experiments, and analysis. The workflow records full feedback and actions, then stops when both the score and readiness criteria are met or the round limit is reached.
Create pixel art illustrations as SVG files, a scalable image format, for READMEs, documentation, and slides. Build character portraits, conversations, or group scenes, then refine colors, speech bubbles, arrows, and spacing to fit the requested layout.
Turn a broad robotics research direction into ranked ideas with concrete benchmarks and simulation plans. The workflow combines literature review, novelty checks, and external critique while accounting for hardware access, safety, evaluation metrics, and failure cases.
Compare an invention with prior art to assess novelty and inventive step, meaning whether its differences would be obvious. Produce claim comparison tables, suggested claim amendments, and a report identifying potential grounds for rejection.
Plan a 10–12 page systems research paper for conferences such as OSDI and SOSP. Get section page budgets, paragraph roles, and writing patterns that connect the research problem, design decisions, and evaluation evidence.
Improve a compiled LaTeX paper through two rounds of Claude review, edits, and recompilation. The workflow addresses inconsistent reasoning, unsupported claims, unclear writing, and visual presentation, while keeping a cumulative log of changes.
Check experimental results before making research claims. A fresh reviewer examines reference data, score calculations, result files, and evaluation scope, then produces an evidence-based report showing which claims are supported and which need qualification.
Find related papers across local PDFs, research notes, and web sources, then summarize their key contributions and relevance. Use existing collections as a starting point, remove duplicates, and search for literature that fills gaps.
Turn a broad research direction into ranked ideas, a refined proposal, and an experiment plan. The workflow combines literature searches, novelty checks, small pilot experiments, and Gemini review to assess evidence and identify useful next steps.
Fill unfinished research-wiki paper pages using summaries and abstracts from external sources. Organize each paper’s problem, method, results, limitations, and reusable ideas while preserving existing content by default and recording which source supplied the information.
Launch machine learning experiments on local GPUs, remote servers, Vast.ai, or Modal. It checks the configured environment, deploys code, saves logs, and verifies startup, with optional W&B metric logging and automatic Vast.ai result collection and instance cleanup.
Plan and run ablation studies, experiments that remove or replace parts of a method to test their contribution. Organize reviewer questions, priorities, expected outcomes, and compute costs, then record results and findings.
Measure scripts, running processes, or whole systems to find performance bottlenecks. Select suitable tools, add measurement code when needed, and report CPU, GPU, memory, and communication findings with prioritized recommendations and a record of file changes.
Explore computer architecture and circuit design settings by repeatedly running programs, measuring results, and adjusting parameters. Compare configurations against a baseline, respect design constraints, and receive a report with the best configuration found and the search history.
Get critical feedback from Claude on research ideas, papers, and experimental results. Through multiple review rounds, identify unsupported claims, missing experiments, and narrative weaknesses, then document agreed conclusions and a prioritized improvement plan.
Run model training, fine-tuning, inference, and batch jobs on Modal’s cloud GPUs. Estimate hardware needs and cost, generate Python launch scripts, run or deploy workloads, monitor logs, and retrieve results without managing remote servers.
Prepare a polished paper for a different venue by addressing prior reviewer concerns through limited text edits. Adapt formatting, check page limits and anonymity, and preserve earlier submissions without adding experiments or changing the bibliography.
Rent and manage vast.ai GPUs based on the training task rather than a chosen hardware model. The skill estimates requirements, compares offers by total expected cost, prepares the selected instance, and retrieves results before destroying it.
Improve an existing LaTeX paper through two rounds of Gemini review, targeted edits, and PDF rebuilding. Check whether claims match the evidence, resolve notation and presentation issues, and retain review logs and PDF versions.
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