open-paper-machine

Activate 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.

ALWAYS 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.

Activate 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 ship code.

Activate 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.

Activate 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.

Activate 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.

Activate 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 principles, 3 specialist agents).

Activate 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 analysis workflows.

Comprehensive 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.

Activate 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.

ALWAYS 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.

Activate 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.

Activate 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).

Activate 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.

Activate 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).

Activate 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.

Activate 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.

Activate 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).