quadas-c-assessment-for-diagnostic-accuracy-studies
Automated bias assessment for diagnostic accuracy studies using QUADAS-C criteria. Requires full text input.
Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Automated bias assessment for diagnostic accuracy studies using QUADAS-C criteria. Requires full text input.
Automates critical appraisal and quality assessment for research papers by analyzing text against established methodological standards (such as risk of bias tools, quality checklists, or reporting guidelines) and synthesizing a structured evaluation report. Use when you need to assess the methodological quality, internal validity, or reporting completeness of any type of study—including RCTs, observational studies, systematic reviews, qualitative research, or diagnostic accuracy studies.
Evaluates bias in medical literature (prognosis studies) using QUAPAS criteria. Use when the user wants to assess the quality or risk of bias of a medical paper text.
Automates Risk of Bias 2 (ROB2) assessment for RCT papers by analyzing text against specific domains and synthesizing a report. Use when you need to assess the quality of a clinical trial paper or evaluate risk of bias.
Automates Risk of Bias 2 (ROB2) assessment for RCT papers by analyzing text against specific domains and synthesizing a report. Use when you need to assess the quality of a clinical trial paper or evaluate risk of bias.
Query the Reactome REST API for pathway content and enrichment analyses; use when you need curated pathway data, reaction details, or overrepresentation results for a gene list.
Find validated alternative reagents based on literature citation data.
Designs a structured real-world evidence study using EHR, claims, or registry data, with explicit handling of time zero, eligibility windows, exposure definitions, outcome windows, censoring, confounding control, and target-trial-emulation logic. Use this skill when the user needs study-type design and protocol framing for an observational clinical study based on routine-care data. Do not invent database fields, follow-up completeness, linkage, coding validity, or causal identifiability.
Automatically finds and ranks PubMed references for each sentence in scientific text; use when you need titles, DOIs, and brief recommendation reasons from the PubMed E-utilities API.
Multi-database literature search and search-strategy design that outputs structured, reproducible result lists; use when you need reference retrieval, systematic searching, review topic selection, or to construct a traceable search strategy.