scholar-conceptual

scholar-conceptual is an Academic writing & papers skill for AI agents, published by joshzyj in the open-scholar-skill repository on GitHub. Skillspace rates scholar-conceptual D (66/100) and it passed the safety scan; the rating is based on static analysis only.

Build original theoretical frameworks and produce publication-quality conceptual diagrams for social science research. Two modes: (1) THEORIZE — construct new theories from empirical puzzles using typology construction (property-space analysis), process theorizing, mechanism specification (Coleman's boat, Hedström DBO), scope condition mapping, multi-level models, abductive inference, and synthetic framework integration; (2) DIAGRAM — generate conceptual figures (mechanism diagrams, multi-level models, typology matrices, process/temporal models, concept maps, feedback loops, scope boundaries) as publication-ready TikZ/PDF or Mermaid/SVG with journal-specific formatting. Distinct from scholar-hypothesis (which selects FROM existing theories to derive testable hypotheses) — this skill builds the theories themselves. Distinct from scholar-causal (which builds DAGs for identification) — this skill represents conceptual relationships, not causal identification.

Grade

D

Quality

66 / 100

Safety

Passed

GitHub stars

102

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