Use when reviewing mathematical validity, evidence, reproducibility, figures or a submission draft.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when planning a modeling solution, selecting the next useful step or briefing a specialist.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Use the following questions in whatever order the task needs. They are prompts for reasoning, not mandatory stages or files.
What decision is the reader trying to make? What is given, unknown or required? Which mechanisms must the solution represent? Check the actual contest rules when applicable, including deadline, page limits and AI-use requirements.
Start with a useful baseline. Define variables, units, assumptions, constraints and the objective. Compare plausible alternatives when there is a real choice; do not invent extra models to meet a quota. Explain why the added complexity changes the answer. Check identifiability, data requirements and limiting cases.
Which observation could disprove the model? Can a simpler baseline perform as well? Test influential assumptions and plausible adverse scenarios. Separate parameter uncertainty, observation noise and structural uncertainty. Match the paper's claims to the implemented mathematics and the data actually used.
Answer the problem's questions with interpretable quantities and limitations. Choose figures from figure presets, including the once-per-task image2 question. Build the explanation around the results, not the history of experiments. Review with review questions.
When delegation is useful and available, give a specialist a bounded question, relevant data, current assumptions and a concrete output. Agree file ownership for concurrent editing. Ask for ordinary prose: finding, reasoning, artifact paths and unresolved uncertainty. The lead integrates the answer and resolves conflicting evidence; it does not collect points or gate every intermediate step.
For a fresh task, a compact prompt is:
Solve the supplied modeling problem. State assumptions, build and test a useful baseline, add justified complexity, and connect each recommendation to evidence. Adapt the workflow to the available time. Select purposeful figures using mathodology-figure-presets and ask once about image2 availability. Keep calculations reproducible and explain what could change the conclusion.
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Use when reviewing mathematical validity, evidence, reproducibility, figures or a submission draft.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when checking skill metadata, references or repository boundaries, or preparing an explicitly requested skills release.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when finding literature, datasets, domain facts, citation details or licensed figure references.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when selecting, designing, generating or reviewing scientific figures, complex modeling charts, paper illustrations or image2-assisted visuals.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when maintaining the skills-only repository or checking whether a change belongs here.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when adding, editing or reviewing skills, role prompts or skill metadata.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.