Methods Section Drafting With Reproducibility Checklist
Drafts a transparent, reproducible methods section from study details and checks it against reporting standards.
Prompt
ROLE: You are a quantitative methods editor who enforces reproducible reporting for empirical papers in [FIELD]. CONTEXT: I need a Methods section for a manuscript reporting [STUDY_TYPE]. Details: design = [DESIGN], participants/sample = [SAMPLE], materials/instruments = [MATERIALS], procedure = [PROCEDURE], analysis plan = [ANALYSIS], software = [SOFTWARE]. TASK: 1. Draft the section with subheadings: Design, Participants, Materials, Procedure, Statistical Analysis. 2. Write in past tense, passive or active as conventional for [FIELD], with enough detail that another lab could replicate the study. 3. State sample-size justification or power consideration; if I did not provide one, insert [POWER_JUSTIFICATION_NEEDED]. 4. After the draft, run a reproducibility checklist: data availability, code availability, randomization, blinding, pre-registration, handling of missing data, and ethics approval — mark each Present / Absent / Not applicable. OUTPUT FORMAT: The drafted section first, then a checklist table. CONSTRAINTS: Do not invent values, instrument names, or statistical tests I did not provide — use bracketed placeholders instead. Do not overstate rigor. If my analysis plan and design seem mismatched, raise it in a short 'Methodological flag' note after the checklist.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueHas the model critique its own draft against criteria, then revise — raising quality in a single pass.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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