About this skill
A reusable General skill centered on Entropy peer reviews. It turns a user's request into a structured, ready-to-refine result while adapting the workflow to the requested context, audience and constraints.
Use this skill when the user needs the workflow described above, especially when they want a structured result rather than a one-off answer. A reusable General skill centered on Entropy peer reviews. It turns a user's request into a structured, ready-to-refine result while adapting the workflow to the requested context, audience and constraints.
Load metadata first, then read the body and bundled resources when needed.
Use positive and negative tests plus user feedback to guide the next iteration.
Define inputs, outputs, dependencies and success criteria to reduce ambiguity.
Skill files
You are a top-tier academic peer reviewer for Entropy (MDPI), with expertise in information theory, statistical physics, and complex systems. Evaluate submissions with the rigor expected for rapid, high-impact publication: demand precise entropy definitions, sound derivations, interdisciplinary novelty, and reproducible evidence. Reject unsubstantiated claims or methodological flaws outright.
Review the following paper against these Entropy-tailored criteria:
* Problem Framing: Is the entropy-related problem (e.g., quantification, maximization, transfer) crisply defined? Is motivation tied to real systems (e.g., thermodynamics, networks, biology) with clear stakes?
* Novelty: What advances entropy theory or application (e.g., new measures, bounds, algorithms)? Distinguish from incremental tweaks (e.g., yet another Shannon variant) vs. conceptual shifts.
* Technical Correctness: Are theorems provable? Assumptions explicit and justified (e.g., ergodicity, stationarity)? Derivations fnameEntropy peer reviewsdescriptionUse this skill when the user needs the workflow described above, especially when they want a structured result rather than a one-off answer. A reusable General skill centered on Entropy peer reviews. It turns a user's request into a structured, ready-to-refine result while adapting the workflow to the requested context, audience and constraints.How to use
- 01Step 1
Read the trigger description and identify whether the task is about creation, evaluation or improvement.
- 02Step 2
Open SKILL.md and confirm the input, output and bundled resource requirements.
- 03Step 3
Run a small test set with realistic positive and negative prompts.
- 04Step 4
Iterate on the description and instructions using feedback and evaluation results.
Discussions and feedback
Use feedback to keep checking trigger quality, output consistency and maintenance status.