Evaluates the quality of cohort studies using the Newcastle-Ottawa Scale (NOS). Use when the user provides a cohort study article or text and needs a quality assessment report.
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Evaluates the quality of cohort studies using the Newcastle-Ottawa Scale (NOS). Use when the user provides a cohort study article or text and needs a quality assessment report.
This skill evaluates the quality of a cohort study based on the Newcastle-Ottawa Scale (NOS). It analyzes Selection, Comparability, and Outcome categories and generates a scored report.
When to Use
Use this skill when the request matches its documented task boundary.
Use it when the user can provide the required inputs and expects a structured deliverable.
Prefer this skill for repeatable, checklist-driven execution rather than open-ended brainstorming.
Key Features
Scope-focused workflow aligned to: Evaluates the quality of cohort studies using the Newcastle-Ottawa Scale (NOS). Use when the user provides a cohort study article or text and needs a quality assessment report.
Packaged executable path(s): scripts/calculate_nos_score.py plus 1 additional script(s).
Reference material available in references/ for task-specific guidance.
Structured execution path designed to keep outputs consistent and reviewable.
Dependencies
See ## Prerequisites above for related details.
Python: 3.10+. Repository baseline for current packaged skills.
Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.
Important: JSON string must be properly escaped when passed via command line.
Step 5: Generate Final Report
Return to user:
The generated Markdown table
Brief explanation of each scoring decision
Summary of study quality (High: ≥7 stars, Moderate: 4-6 stars, Low: <4 stars)
Key strengths and limitations
Helper Scripts
PDF Text Extraction
When the user provides a PDF file path, use scripts/extract_pdf.py to extract the text content before assessment:
Features:
Extracts text from all pages
Saves output to extracted_text.txt
Handles path issues with spaces
Provides progress feedback
Usage:
python scripts/extract_pdf.py "path/to/file.pdf"
Output:
Console: Extraction progress and statistics
File: extracted_text.txt in current working directory
Quality Interpretation
Score
Quality Level
Recommendation
9 stars
Excellent
Low risk of bias, high confidence
7-8 stars
High quality
Acceptable for meta-analysis
4-6 stars
Moderate quality
Consider in sensitivity analyses
<4 stars
Low quality
High risk of bias, use caution
Common Issues and Solutions
PDF extraction fails: Check if file exists and is not corrupted; try different PDF library (PyMuPDF)
JSON parsing error: Ensure proper escaping of quotes in command line
Uncertain criteria: When in doubt, be conservative and assign "-"
Missing information: Note in report that certain items could not be assessed
Input Validation
This skill accepts requests that match the documented purpose of cohort-study-quality-assessment-nos and include enough context to complete the workflow safely.
Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:
cohort-study-quality-assessment-nos only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
References
Detailed criteria: references/nos_criteria.md
Wells GA, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses
When Not to Use
Do not use this skill when the required source data, identifiers, files, or credentials are missing.
Do not use this skill when the user asks for fabricated results, unsupported claims, or out-of-scope conclusions.
Do not use this skill when a simpler direct answer is more appropriate than the documented workflow.
Required Inputs
A clearly specified task goal aligned with the documented scope.
All required files, identifiers, parameters, or environment variables before execution.
Any domain constraints, formatting requirements, and expected output destination if applicable.
Output Contract
Return a structured deliverable that is directly usable without reformatting.
If a file is produced, prefer a deterministic output name such as cohort_study_quality_assessment_nos_result.md unless the skill documentation defines a better convention.
Include a short validation summary describing what was checked, what assumptions were made, and any remaining limitations.
Validation and Safety Rules
Validate required inputs before execution and stop early when mandatory fields or files are missing.
Do not fabricate measurements, references, findings, or conclusions that are not supported by the provided source material.
Emit a clear warning when credentials, privacy constraints, safety boundaries, or unsupported requests affect the result.
Keep the output safe, reproducible, and within the documented scope at all times.
Failure Handling
If validation fails, explain the exact missing field, file, or parameter and show the minimum fix required.
If an external dependency or script fails, surface the command path, likely cause, and the next recovery step.
If partial output is returned, label it clearly and identify which checks could not be completed.
Quick Validation
Run this minimal verification path before full execution when possible:
python scripts/calculate_nos_score.py --help
Expected output format:
Result file: cohort_study_quality_assessment_nos_result.md
Validation summary: PASS/FAIL with brief notes
Assumptions: explicit list if any
