Source: https://github.com/aipoch/medical-research-skills
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: Generates the "Risk of Bias" results section for a meta-analysis based on assessment tables and statistics. Use when the user wants to draft the risk of bias analysis text from provided data tables.
- Packaged executable path(s):
scripts/format_result.py plus 1 additional script(s).
- Structured execution path designed to keep outputs consistent and reviewable.
Dependencies
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.
Example Usage
cd "20260316/scientific-skills/Academic Writing/meta-results-risk-of-bias"
python -m py_compile scripts/format_result.py
python scripts/format_result.py --help
Example run plan:
- Confirm the user input, output path, and any required config values.
- Edit the in-file
CONFIG block or documented parameters if the script uses fixed settings.
- Run
python scripts/format_result.py with the validated inputs.
- Review the generated output and return the final artifact with any assumptions called out.
Implementation Details
See ## Workflow above for related details.
- Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
- Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
- Primary implementation surface:
scripts/format_result.py with additional helper scripts under scripts/.
- Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
- Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.
Validation Shortcut
Run this minimal command first to verify the supported execution path:
python scripts/format_result.py --help
Risk of Bias Results Generator
This skill generates a professional, academic "Risk of Bias" results section for a meta-analysis. It analyzes the provided statistics and detailed assessment table, drafts the text using a clinical expert persona, and automatically formats the output with necessary figure citations.
When to Use This Skill
Use this skill when the user provides:
- Title: The title of the meta-analysis.
- Language: Target language (Chinese or English).
- Statistics: A summary table of bias risk assessment.
- Detailed Assessment Table: Detailed scores for each study across domains (D1-D5).
And asks for:
- A draft of the "Results" section regarding risk of bias.
- An analysis of the bias risk.
Workflow
- Draft Text: Analyze the input tables and draft an academic summary (>300 words).
- Summarize overall risk (High, Some concerns, Low).
- Analyze each domain (D1-D5) specifically.
- Use specific numbers from the statistics table.
- Format Output: Automatically insert the figure citation
(Figure 1) before the last punctuation and append the figure caption.
Usage Instructions
1. Draft the Content
Use the following prompt to generate the initial text:
Role: Clinical Medical Expert
Task: Write an academic "Results" section based on the following inputs:
- Title: {{title}}
- Detailed Assessment Table: {{Detailed_Assessment_Table}}
- Statistics: {{statistics}}
Requirements:
- Explicitly state the total number of studies evaluated.
- First, summarize the Overall bias risk (High, Some concerns, Low).
- Then, analyze each domain (D1-D5) specifically.
- Use specific numbers from the statistics table.
- Maintain a professional, objective, academic style.
- Length: >300 words.
- Language: {{language}}
2. Format the Result
Run the formatting script to insert the figure citation and caption.
python scripts/format_result.py --text "<generated_text>" --language "{{language}}"
Tools and Scripts
scripts/format_result.py: Inserts (Figure 1) and appends the figure placeholder and caption.
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
meta_results_risk_of_bias_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.
Input Validation
This skill accepts requests that match the documented purpose of meta-results-risk-of-bias 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:
meta-results-risk-of-bias only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
Quick Validation
Run this minimal verification path before full execution when possible:
python scripts/format_result.py --help
Expected output format:
Result file: meta_results_risk_of_bias_result.md
Validation summary: PASS/FAIL with brief notes
Assumptions: explicit list if any
Deterministic Output Rules
- Use the same section order for every supported request of this skill.
- Keep output field names stable and do not rename documented keys across examples.
- If a value is unavailable, emit an explicit placeholder instead of omitting the field.
Completion Checklist
- Confirm all required inputs were present and valid.
- Confirm the supported execution path completed without unresolved errors.
- Confirm the final deliverable matches the documented format exactly.
- Confirm assumptions, limitations, and warnings are surfaced explicitly.