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 is human-reviewed 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.
12 prompts
Name your product and its competitors and get a rigorous side-by-side teardown across positioning, features, pricing, and gaps — ending in a clear wedge you can actually own. The analysis that turns a vague sense of the market into a real strategy.
Paste a set of papers and get a structured synthesis — not a paper-by-paper summary, but four to six cross-cutting themes plus the open questions the field hasn't answered. The map that shows where the research agrees, conflicts, and still has room.
Name a product and get a defensible TAM, SAM, and SOM estimate built both top-down and bottom-up, with the assumptions spelled out so the number survives scrutiny. The market-size slide that holds up in a pitch instead of getting picked apart.
Paste interview transcripts and get the top five decision-ready insights — the things that recur or matter most — each backed by a real quote from the calls. Pulls the signal out of hours of conversation so the team acts on patterns, not the loudest anecdote.
Name a topic and get a thirty-minute interview guide that surfaces real behavior and motivation without leading the witness. Open-ended, well-sequenced questions that get people talking about what they actually do, not what they think you want to hear.
Give one observation and get five distinct, testable hypotheses that could explain it — each paired with a metric and a way to test it. Turns a curious what-just-happened into a real experiment plan instead of a single hunch you fixate on.
Describe your research question and the shape of your data, and get the right statistical test to use, why it fits, and the assumptions to check first. The thirty-second answer to a question that otherwise sends you back to a textbook.
Name your research goal and get ten clean, unbiased survey questions built to produce analyzable data — free of leading, double-barreled, and loaded phrasing. The difference between results you can trust and a dataset quietly skewed by the wording.
Ask a plain-English question and give it your schema, and get one correct SQL query that answers it — joins, filters, and grouping handled. The bridge from what you want to know to the query that returns it, no SQL fluency required.
Paste a pile of scattered signals and get a sharp one-page trend brief that ties them into a single coherent story — what's happening, why now, and what it means for you. Synthesis, not a list, so the pattern is actually usable.
Describe a messy dataset and get a concrete cleaning and validation plan — how to handle each column's issues, what to standardize, and which checks to run before analysis. A clear path from raw and broken to something you can actually trust.
Describe your data and the message you want it to land, and get the single chart type that communicates it best, with the reasoning and what to avoid. Stops you from defaulting to a bar chart when the story actually calls for something else.
Prompt Dock's Research & Data category collects them, with every prompt human-reviewed 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, with human review checking that 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.