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Claude Skills by TobiasBlask
github.com/TobiasBlask41 skills1 installs87 views
- Citation ManagementComprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.Votes: 0GitHub stars: 18
- Consciousness CouncilRun a multi-perspective Mind Council deliberation on any question, decision, or creative challenge. Use this skill whenever the user wants diverse viewpoints, needs help making a tough decision, asks for a council/panel/board discussion, wants to explore a problem from multiple angles, requests devil's advocate analysis, or says things like "what would different experts think about this", "help me think through this from all sides", "council mode", "mind council", or "deliberate on this". Als...Votes: 0GitHub stars: 18
- Exploratory Data AnalysisPerform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scien...Votes: 0GitHub stars: 18
- Get Available ResourcesThis skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before runni...Votes: 0GitHub stars: 18
- Hypothesis GenerationStructured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.Votes: 0GitHub stars: 18
- Literature ReviewConduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).Votes: 0GitHub stars: 18
- Markdown Mermaid WritingComprehensive markdown and Mermaid diagram writing skill. Use when creating any scientific document, report, analysis, or visualization. Establishes text-based diagrams as the default documentation standard with full style guides (markdown + mermaid), 24 diagram type references, and 9 document templates.Votes: 0GitHub stars: 18
- MatplotlibLow-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.Votes: 0GitHub stars: 18
- NetworkxComprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.Votes: 0GitHub stars: 18
- Peer ReviewStructured manuscript/grant review with checklist-based evaluation. Use when writing formal peer reviews with specific criteria methodology assessment, statistical validity, reporting standards compliance (CONSORT/STROBE), and constructive feedback. Best for actual review writing, manuscript revision. For evaluating claims/evidence quality use scientific-critical-thinking; for quantitative scoring frameworks use scholar-evaluation.Votes: 0GitHub stars: 18
- PlotlyInteractive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization.Votes: 0GitHub stars: 18
- PyzoteroInteract with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3. Use this skill when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.Votes: 0GitHub stars: 18
- Research GrantsWrite competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.Votes: 0GitHub stars: 18
- Scholar EvaluationSystematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.Votes: 0GitHub stars: 18
- Scientific BrainstormingCreative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.Votes: 0GitHub stars: 18
- Scientific Critical ThinkingEvaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.Votes: 0GitHub stars: 18
- Scientific SchematicsCreate publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.Votes: 0GitHub stars: 18
- Scientific VisualizationMeta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.Votes: 0GitHub stars: 18
- Scientific WritingCore skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage process with (1) section outlines with key points using research-lookup then (2) convert to flowing prose. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA), for research papers and journal submissions.Votes: 0GitHub stars: 18
- SeabornStatistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.Votes: 0GitHub stars: 18
- Statistical AnalysisGuided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.Votes: 0GitHub stars: 18
- StatsmodelsStatistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.Votes: 0GitHub stars: 18
- Venue TemplatesAccess comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and grant proposals (NSF, NIH, DOE, DARPA). This skill should be used when preparing manuscripts for journal submission, conference papers, research posters, or grant proposals and need venue-specific formatting requirements and templates.Votes: 0GitHub stars: 18
- What If OracleRun structured What-If scenario analysis with multi-branch possibility exploration. Use this skill when the user asks speculative questions like "what if...", "what would happen if...", "what are the possibilities", "explore scenarios", "scenario analysis", "possibility space", "what could go wrong", "best case / worst case", "risk analysis", "contingency planning", "strategic options", or any question about uncertain futures. Also trigger when the user faces a fork-in-the-road decision, want...Votes: 0GitHub stars: 18
- Audit EngineActivate when the user wants to audit a paper's empirical or technical claims against a linked code repository — checking whether experiments, datasets, models, metrics, and hyperparameters described in the paper actually exist and match the code. Produces a structured audit report classifying each claim as CONFIRMED, PARTIAL, MISSING, or MISMATCH, with file/line evidence. Useful for reproducibility checks, reviewer due diligence, and pre-submission self-audits of ML/CS/empirical papers that ...Votes: 0GitHub stars: 18
- Coauthor EngineActivate when the user needs to manage multi-author collaboration on a paper. Tracks author contributions using the CRediT taxonomy, manages responsibility assignments, documents the human-AI division of labor, and produces an author contribution statement ready for submission.Votes: 0GitHub stars: 18
- Figure EngineActivate when the user needs to generate, refine, or evaluate academic figures, diagrams, or statistical plots. Uses PaperBanana to transform text descriptions or data files into publication-quality illustrations via direct Python API call. Fallback: matplotlib/seaborn.Votes: 0GitHub stars: 18
- Idea EngineActivate when the user needs to evaluate whether a research idea is worth pursuing, brainstorm new research directions, or stress-test a paper concept before committing. This is Phase 0 of the paper machine — the gate that decides whether the full 8-phase pipeline should run. Also activates standalone via /evaluate-idea. Integrates Carlini's research philosophy (conclusion-first test, taste for problems, kill conditions, unreasonable effort) with structured evaluation (7 dimensions, RS1-RS8 ...Votes: 0GitHub stars: 18
- Latex EngineActivate when the user wants to export a completed paper draft to production-ready LaTeX (.tex) and PDF. Converts draft.md + references.bib + figures/ into a complete arxiv-style LaTeX project with properly resolved \citep/\citet citations, booktabs tables, figure environments, and compiled PDF output.Votes: 0GitHub stars: 18
- Literature EngineALWAYS activate when the user needs to find, organize, review, or synthesize academic literature. Uses academic APIs (Semantic Scholar, OpenAlex, CrossRef, arXiv) via scripts/academic_search.py. Handles search strategy, snowballing, screening, concept matrices, narrative synthesis, and literature monitoring (detecting new publications since last search). NEVER use web scraping for paper discovery — APIs first, web search only for verification.Votes: 0GitHub stars: 18
- Method EngineActivate when the user needs to select, justify, describe, or execute a research methodology. Provides method selection guidance, complete method section templates, quality criteria, and tool recommendations. Covers SLR, qualitative (case study, Gioia, Mayring, Grounded Theory), quantitative (SEM, regression, survey, experiment), DSR, mixed methods, action research, ethnography, Delphi study, and simulation. Also includes Research Data Management (RDM) guidance for FAIR-compliant data handling.Votes: 0GitHub stars: 18
- Peer Review EngineActivate when the user wants to simulate a double-blind peer review of their paper before submission or before sharing with co-authors. Reads the current draft (draft.md or paper.tex), generates 2 independent reviewer reports in the style of top IS/CS conferences (ICIS, ECIS, MISQ level), and saves the output as simulated_reviews.md. The output is formatted to serve as direct input for /respond-reviewers (review-engine feedback loop).Votes: 0GitHub stars: 18
- Positioning EngineActivate when the user needs to analyze how their paper positions itself relative to the closest existing work. Builds a differentiation matrix, identifies unique positioning, and generates a positioning statement that strengthens the contribution argumentation. Complements the theory-engine by focusing on the competitive landscape of related papers.Votes: 0GitHub stars: 18
- Presentation EngineActivate when the user needs to create conference presentation slides from a completed paper. Extracts key content, designs a slide structure, generates slide content with speaker notes, and produces a presentation-ready markdown file. Supports IS/CS conference formats (15-20 min presentations).Votes: 0GitHub stars: 18
- Qualitative EngineActivate when the user needs to analyze qualitative data — interview transcripts, field notes, or open-ended survey responses. Handles structured summarization, thematic coding, cross-case analysis, theme matrices, and evidence retrieval. Designed to solve the context-window problem: generates compact summaries first, then works from summaries instead of full transcripts. Only loads full text when specific quotes are needed. Supports Gioia, Mayring, Grounded Theory, and general thematic analy...Votes: 0GitHub stars: 18
- Review EngineActivate when the user provides reviewer or co-author feedback (annotated PDF, pasted comments, or reviewer report) and wants to implement revisions. Extracts review points, maps them to paper.tex locations, classifies actions, implements changes, recompiles, and generates a change log + latexdiff. Handles the full revision loop from feedback to committed changes.Votes: 0GitHub stars: 18
- Screening EngineActivate when the user needs to systematically screen papers for a Systematic Literature Review (SLR). Implements the PRISMA-compliant screening pipeline: define inclusion/exclusion criteria, title/abstract screening, full-text screening, quality assessment, and PRISMA flow diagram generation. Takes the literature_base.csv from Phase 1 (Reconnaissance) and produces a filtered, documented, auditable set of included studies.Votes: 0GitHub stars: 18
- Submission EngineActivate when the user wants to prepare a paper for submission to a specific venue. Handles venue-specific formatting validation, anonymization checks for double-blind review, cover letter generation, suggested reviewer identification, and submission checklist completion. Produces a submission-ready package.Votes: 0GitHub stars: 18
- Theory EngineActivate when the user needs to select a theoretical lens, formulate a research gap, derive hypotheses or design principles, or write a contribution statement. Provides concrete theory-to-paper templates, not abstract advice.Votes: 0GitHub stars: 18
- Verification EngineActivate when the user needs to verify citations, check source accuracy, or validate that referenced papers actually support the claims attributed to them. Retrieves source abstracts and full text (for open-access papers), compares each citation claim against actual source content, and produces a structured verification report with classifications (VERIFIED, PLAUSIBLE, MISMATCH, UNVERIFIABLE, NOT FOUND).Votes: 0GitHub stars: 18
- Writing EngineALWAYS activate when the user writes, drafts, or revises any part of an academic paper. This is the core skill for overcoming writer's block and producing complete first drafts. Provides concrete sentence-level templates, paragraph formulas, and section blueprints for IS/WI/BWL research papers. Works for journal papers (MISQ, BISE, EJIS), conference papers (ICIS, ECIS, WI), and working papers.Votes: 0GitHub stars: 18