Research and data AI prompts are careful instructions that get Claude or GPT to read, structure, and question information the way a researcher would. On Prompt Dock they cover real tasks: summarizing papers, extracting key findings, comparing sources, building literature matrices, generating interview questions, and turning raw notes into structured analysis. Every prompt a member submits is reviewed by a person before it goes live, so the reasoning steps are explicit rather than glossed over. Free and premium prompts are both available, and you can reveal any prompt and run it live in the Playground on your own material to check how it handles nuance before you rely on the output.
15 prompts
LLMs are lazy. You have to flog them to do work, you can't just ask them a question. For anything, this will make the LLM dig into all sides.
Daily de-bias for Grok. Irish True versus Lawyer True, five states of truth, and the Ten Commandments restated for a model that worships Logos. Steelman both sides. Echo chambers count as one vote.
Analyze your idea from 50 user, buyer, founder, investor, employee, and technical perspectives in one response. Get hypothetical reactions and probing questions, then answer them to receive a transparent satisfaction score, evidence gaps, and practical next steps.
Tell it your topic, discipline, and scope and get a defensible search strategy — concept map with synonyms, Boolean strings per database, recommended databases, inclusion/exclusion criteria, and a PRISMA-compatible screening workflow. For students and researchers starting a review under deadline.
Locate the earliest evidence loss in a retrieval trace and propose controlled experiments instead of random tuning.
Paste a literature review, meta-analysis, or research summary and get a categorized map of unanswered questions, understudied populations, conflicting findings, and methodological holes — each rated by how tractable it is. The starting point for a dissertation topic or grant proposal.
Paste open-ended survey answers or interview transcripts and get a rigorous thematic analysis — named themes with verbatim quotes, honest frequency bands, a key-tensions section, and goal-tailored recommendations. Built for UX, research, and product teams who need rigor at speed.
Specify a retrieval pipeline that preserves source evidence, enforces access, and explains when an answer is unsupported.
Classify observed failures, separate evidence from hypotheses, and produce anchored grading criteria and regression cases.
Paste any unstructured text — scattered notes, an email thread, a wall of specs — and get a clean table with the columns you define, where missing data is marked, not invented. Outputs Markdown, CSV, or JSON with extraction notes so you know what to verify.
Paste two articles, papers, or reports on the same topic and get a structured comparison — where they agree, where they truly conflict, what each covers alone, and which to trust more and why. Ends with a synthesis a careful reader would actually stand behind.
Turn product rules and representative examples into a compact, reviewable evaluation set before release.
Paste a set of specific claims — from a thread, an article, a pitch deck — and get each one sorted into supported, contested, contradicted, unfalsifiable, or needs-context, with a nuance note for the technically-true-but-misleading ones and an honest disclaimer about the limits of an AI check.
Paste any research paper or abstract and get a clear, jargon-free breakdown of the question, method, finding, and implication — plus a one-sentence takeaway and a caveats flag for sample size, funding, and replication. Built for non-specialists who need to use the evidence, not just admire it.
Check whether an answer's citations actually support its claims and rewrite unsupported portions without guessing.
Prompt Dock's Research & Data category collects them, with every prompt a member submits reviewed by a person before it publishes. Reveal the full instructions, pick free or premium, and run each in the Playground on your own paper or dataset so you can verify how it summarizes and reasons before trusting it for real work.
Claude is well suited to long documents, careful summarization, and structured reasoning, while GPT is handy for quick extraction and brainstorming angles. Research prompts note a recommended model, and the Playground lets you run the same prompt on your source to compare which handles the detail best.
They're built for it: the instructions ask for structured, faithful summaries rather than loose paraphrase. Run one in the Playground on your actual paper to confirm it captures the findings and caveats you care about before you cite or act on the summary.