Keep research progress, decisions, and pending checkpoints across sessions. Store project context locally, recover essential details when returning, and track why decisions changed so research work can resume with a clear next step.
Plan literature searches for six review types, from systematic to rapid reviews. Develop database-specific search queries, selection criteria, citation tracking, and search records, while comparing approaches for coverage, reproducibility, and available time.
Find and compare academic journals using a research abstract, field, and publication priorities. The skill combines topic fit, citation metrics, open access options, and practical considerations into a comparison report, sequential submission plan, and cover letter template.
Choose quantitative or qualitative methods that fit a research question and dataset. Compare alternatives, check assumptions, generate analysis code, interpret results, and examine sensitivity, meaning how conclusions change under different analytical choices.
Coordinate research from question development through literature searches, analysis, and publication with specialized agents. Supports quantitative, qualitative, and mixed methods studies, plus systematic reviews, with human approval at key decisions about research direction and methods.
Review code changes and pull requests for correctness, security, performance, and test quality. The skill helps prioritize issues, write specific and constructive feedback, and create shared review checklists and standards for a development team.
Compare original and rewritten academic text to check that citations, statistics, and core claims remain intact. Receive a report covering writing quality, scholarly tone, and whether the changes should be approved, reviewed, or rejected.
Combine interview themes and numerical findings into comparison tables and integrated conclusions. The skill helps select an integration approach, explain agreements and contradictions, and assess whether conclusions are supported by both kinds of evidence.
Find your way around Diverga with a guide to its 24 research agents across nine categories. View commands, example requests, direct invocation syntax, and checkpoints where people review research decisions, with recommendations based on research context.
Build web pages, application interfaces, and components with a clear visual direction suited to their purpose and audience. It turns design choices about typography, color, layout, and motion into working frontend code with consistent visual details.
Learn from top Kaggle solutions across text, images, time series, tabular data, and multimodal tasks that combine data types. Explore technical analyses, model settings, reusable code templates, and practical lessons to inform machine learning projects.
Plan quantitative research by comparing experiments and surveys against research goals and resource limits. Get design recommendations, sample size calculations, participant recruitment strategies, and experimental materials, with an assessment of factors that could distort results.
Apply a compact checklist to everyday code changes. Read existing files first, keep edits focused, check types and security, verify execution, remove debugging leftovers, and summarize what changed and its impact.
Assess study quality and risk of bias, meaning systematic distortions in research results. Choose assessment tools suited to the study and review purpose, document judgment rationales, and summarize evidence certainty and recommendations for use in further analysis.
Co-write proposals, technical specifications, and decision documents through context gathering, section-by-section drafting, and revision. A fresh AI reader then tests the document to reveal unclear explanations, missing context, and contradictions before it is shared.
Revise formulaic academic prose through staged vocabulary and structure edits while checking that citations, statistics, and technical terms remain intact. Choose sections and editing intensity, compare changes, and review progress before accepting the revised manuscript.
Collect papers across research databases, turn research questions into targeted search queries, remove duplicate records, and extract available PDF links. Useful for preparing systematic literature reviews, with database selection and access checks before retrieval.
Configure a terminal status display for Diverga research projects. Show the project name, research stage, checkpoint progress, and memory health, choose among four display presets, and set up or repair the Claude Code integration.
Design studies that combine quantitative data, such as surveys, with qualitative evidence, such as interviews. It recommends a suitable design and outlines study phases, participant selection, timing, and ways to combine findings into an integrated interpretation.
Review research ethics, participant protection, and potential bias from planning through publication. The skill examines questionable research practices and study trustworthiness, then produces a structured report with evidence, risk levels, and prioritized recommendations.
Helps build a research framework by comparing theories, mapping relationships between variables, and deriving testable hypotheses. Explores less conventional options, examines weaknesses and competing explanations, and produces diagrams with anticipated reviewer objections.
Build Claude Code plugin hooks: automated checks triggered by tool use or session events. Get guidance on prompt and command hooks for validating actions, checking task completion, loading context, and testing configurations.
Organize interview transcripts and other qualitative material into codes, or meaning labels, and broader themes. Develop coding guidelines, compare researchers’ coding decisions, and document whether additional data still introduces new findings.
Prepare research papers for RAG, a method that supplies retrieved documents to AI. Download PDFs, extract and split text, and build a local searchable database, with parallel processing for document batches.
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