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SkillsMP는 zjunlp/AutoSciRub에서 8개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
수집된 skill 8개 중 8개를 표시합니다.
Coordinate the full AutoSciRub workflow for autonomous scientific research tasks. Use when a user wants to turn an underspecified research instruction into an executable rubric, guide research execution, verify a report criterion by criterion, and run…
원문 언어: 영어
Verify a scientific report and supporting artifacts against an AutoSciRub executable rubric criterion by criterion. Use after execution has produced a report, code, results, tables, figures, or other artifacts, when Codex needs strict satisfaction labels,…
원문 언어: 영어
Synthesize a task-specific executable scientific rubric from an instruction-derived skeleton, literature grounding, and task-data profile. Use in AutoSciRub when Codex needs criteria with linked goals, data sources, required analyses, metrics, comparisons,…
원문 언어: 영어
Convert PDFs and paper-like documents into Markdown with MinerU before reading or analyzing them. Use when AutoSciRub or another scientific agent needs to inspect local or remote PDFs, equations, tables, or scanned papers where direct PDF text extraction…
원문 언어: 영어
Induce an instruction-derived scientific goal skeleton from a research task before reading literature, web sources, data details, code, or prior results. Use at the start of AutoSciRub when Codex needs atomic, traceable goals that state what the task should…
원문 언어: 영어
Ground an AutoSciRub rubric skeleton in scientific literature and authoritative documentation. Use after rubric_skeleton.json exists when a research agent needs goal-centered methods, protocols, metrics, baselines, controls, robustness checks, and evidence…
원문 언어: 영어
Perform one AutoSciRub targeted revision round using failed executable-rubric criteria and criterion-level verification feedback. Use when Codex needs to update a research artifact by adding missing experiments, comparisons, evidence, analysis, figures,…
원문 언어: 영어
Build a lightweight task-visible data and resource profile for AutoSciRub. Use after rubric skeleton and literature grounding when Codex needs to inspect available files, datasets, code, schemas, units, labels, tools, constraints, and goal feasibility before…
원문 언어: 영어