From car-skills
Builds the conceptual engine of a CAR manuscript: economic/behavioral mechanism, predictions/hypotheses, or formal model, adapted to archival, experimental, analytical, or qualitative traditions.
How this skill is triggered — by the user, by Claude, or both
Slash command
/car-skills:car-theory-developmentThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
- Predictions are descriptive ("X is associated with Y") with no mechanism
Because CAR is method-agnostic, "theory development" means different things across its traditions, and a reader should never be able to swap in a generic management-theory template:
Use this as a second-pass capability check. First lock the accounting construct, setting, identification or theory, and disclosure/market/organizational implication; then test whether the manuscript addresses accounting reviewers who expect accounting-specific constructs, credible design, and contribution to reporting, auditing, tax, or governance debates.
claim / evidence / blocker / next edit rows so the next pass can patch the manuscript directly.resources/official-source-map.md for volatile rules and name the one unresolved fact that could change the recommendation.【Tradition】archival / experimental / analytical / qualitative
【Mechanism】the economic/behavioral logic ...
【Predictions/Hypotheses】H1..Hn, signs, conditional/cross-sectional ...
【Assumptions】maintained vs. tested (or model primitives) ...
【Process】predicted mediator / equilibrium intuition ...
【Next step】car-literature-positioning or car-methods
npx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin car-skillsFrames results as an explicit contribution for a Contemporary Accounting Research manuscript, adapting to archival, experimental, or analytical traditions.
Develops economic mechanisms, analytical models, and testable predictions for TAR manuscripts. Trigger when predictions lack economic logic or a friction is needed.
Builds economic mechanisms and derives signed, falsifiable predictions for JAR manuscripts using information economics, contracting, and disclosure theory.