Run data analytics and produce publication-quality tables and visualizations for social science research. Saves regression tables (HTML/TeX/docx), figures (PDF/PNG), an internal analysis log, and a publication-ready Results document (prose + table notes + figure captions). Accepts file paths, inline/pasted data, or fetches from online sources (NHANES, IPUMS, GSS, World Bank, etc.). Runs A9/B9 verification subagents to check analytic and visualization correctness. For causal designs, invokes /scholar-causal first. Use after /scholar-design.
Automatic quality auditor and continuous improvement engine for the scholar-skill suite. Four modes: (1) OBSERVE — post-skill output audit (run after any skill); (2) AUDIT — skill-suite structural health check; (3) IMPROVE — propose and apply fixes to skill definitions; (4) EVOLVE — cross-session pattern analysis and systemic improvements. Designed to run automatically at the end of any scholar-skill invocation.
Stable, deterministic social-science research-paper pipeline from idea or data to verified manuscript, citations, replication package, and final md/docx/tex/pdf outputs. Use when the user wants a reliable end-to-end auto-research chain that avoids the evolving scholar-full-paper workflow.
Generate research questions from existing materials — codebooks, survey questionnaires, datasets, or published papers/abstracts. Three modes: DATA (data files with safety scan + empirical signal tests), MATERIALS (codebook/questionnaire only with theory-driven ranking), PAPER (published paper/abstract → follow-up research ideas via SciThinker-30B + multi-agent evaluation). Auto-detects mode from file extensions. Explores the data landscape and proposes a ranked Top 10 list of publishable research questions using multi-agent evaluation. PAPER mode optionally uses SciThinker-30B (OpenMOSS-Team/SciThinker-30B on HuggingFace) for scientific ideation generation.
Comprehensive causal inference toolkit for social science research. Covers DAG construction, method selection, and thirteen identification strategies (OLS, DiD, RD, IV, FE, matching/reweighting, synthetic control, causal mediation, staggered DiD, DML/causal forests, bunching estimation, shift-share/Bartik instruments, distributional/quantile methods) — each with assumptions, diagnostics, R code, Stata code, and a write-up template. Use when the user needs to select and justify a causal identification strategy, build a causal DAG, or write the identification argument in their Methods section. Works between /scholar-hypothesis and /scholar-design.
Full citation management for social science manuscripts. Eight modes: (1) INSERT — add in-text citations to uncited claims; (2) AUDIT — find orphans, missing refs, year/author mismatches, duplicates; (3) CONVERT-STYLE — convert between styles (ASA, APA, numbered, author-date); (4) FULL-REBUILD — inventory claims → search Zotero + CrossRef → insert → assemble → audit; (5) VERIFY — verify each ref against local library (Zotero/Mendeley/BibTeX/EndNote), CrossRef, WebSearch; VERIFIED/UNVERIFIED/CORRECTED; (6) EXPORT — generate BibTeX .bib for LaTeX with cite keys, DOIs, enriched metadata; (7) RETRACTION-CHECK — cross-reference Retraction Watch; flag and suggest replacements; (8) REPORTING-SUMMARY — pre-filled NHB/NCS Reporting Summary (design, statistics, data availability) for Nature Human Behaviour and NCS. ABSOLUTE RULE: never fabricate — every reference verified against ≥1 authoritative database; local library searched first. Flags unsupported claims SOURCE NEEDED. Saves complete draft + audit log.
Systematic multi-agent code review of all analysis scripts produced in a project. 6 specialized agents review for: (1) correctness & logic errors, (2) robustness & defensive coding, (3) statistical implementation fidelity, (4) reproducibility & replication readiness, (5) code style & AI-generated anti-patterns, (6) data handling & variable construction (miscoded categories, wrong recodes, mishandled missing values, sample restrictions). Produces a consolidated review report with severity-ranked issues, fix checklist, and a per-script scorecard. Run after /scholar-analyze, /scholar-compute, or /scholar-eda to catch coding errors before manuscript drafting.
Multi-author research collaboration management. Covers CRediT role assignment, task delegation and tracking, co-author communication templates, contribution documentation, version management, conflict resolution, mentoring frameworks for student collaborators, and team coordination for multi-site or multi-PI projects. Use when managing a research team or preparing multi-author submissions.