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Research Claim Source Check

Use Research Claim Source Check to turn real workflow notes into structured chat output for review, decisions, and next actions.

ResearchSource CheckClaims
Preview

Chat Prompt

Recommended model

Gemini 3 Pro

Output format

Structured chat output

Preview

Chat Prompt

chat thread

Claims: creators prefer one AI workspace, video prompts convert better than model pages, and audio templates are underused.

Supported if measured: video prompt conversion can be stated only if analytics compare prompt and model pages. Weak claim: creators prefer one workspace needs survey or behavioral evidence. Missing evidence: audio template usage needs traffic, click, and completion data by mode. Safer wording: early signals suggest workflow pages may reduce decision friction. Next evidence: compare mode-level CTR, first-run completion, and repeat usage.

Output

Supported / Weak / Missing / Safer wording / Evidence

Preview for Research Claim Source Check, focused on input context, structured reply, and actionable next steps.

Full prompt

Research Claim Source Check

Research Claim Source Check chat prompt with structured analysis, risks, recommendations, and next actions.

Recommended model: Gemini 3 ProOutput format: Structured chat output
Full prompt
Chat Prompt
You are a research editor. Review the user's claims and separate supported claims, weak claims, missing evidence, and safer wording.

Usage notes

Add real context, constraints, target reader, current evidence, and expected output depth before running; do not use it as a generic chat question.

Prompt FAQ

Before you use this prompt

Quick checks for inputs, model fit, and how to adapt the template without weakening the result.

What should I prepare before using Research Claim Source Check?

Prepare real input notes, the business goal, constraints, available evidence, and the exact structure you want back.

How should I judge the response quality?

Check whether the reply separates facts from assumptions and gives risks, tradeoffs, and actionable next steps instead of generic advice.

Thread preview

Claims: creators prefer one AI workspace, video prompts convert better than model pages, and audio templates are underused.
Supported if measured: video prompt conversion can be stated only if analytics compare prompt and model pages. Weak claim: creators prefer one workspace needs survey or behavioral evidence. Missing evidence: audio template usage needs traffic, click, and completion data by mode. Safer wording: early signals suggest workflow pages may reduce decision friction. Next evidence: compare mode-level CTR, first-run completion, and repeat usage.

Output

Supported / Weak / Missing / Safer wording / Evidence

More prompts in this mode

chat thread

We want to build an AI assistant for small ecommerce teams that turns product photos into campaign assets.

Problem hypothesis: small ecommerce teams lose time turning raw product photos into channel-ready campaign assets. Riskiest assumptions: photo quality is high enough, teams trust AI asset variation, and review time is the real bottleneck. Research questions: who owns campaign asset creation, where revisions stall, and what quality bar blocks publishing. Validation plan: interview 5 operators, test 3 prompt-led asset flows, and compare time-to-first-approved asset. Decision gate: continue only if teams can reach a publishable draft faster than their current workflow.

chat thread

We are exploring a new AI notes product for solo consultants. Help me turn this into a research brief.

Objective: define whether solo consultants need an AI notes workspace or a lighter client-follow-up layer. Working assumptions: they already capture notes, but synthesis and next-step drafting are inconsistent. Audience: solo consultants with recurring client calls and limited operations support. Key questions: which notes become billable work, what gets lost after calls, and where CRM tools feel too heavy. Research plan: run 6 interviews, review 10 recent call-note workflows, and test one follow-up brief prototype.

chat thread

Here is the outline for our AI product landing page. Tell me what is unclear before we design it.

Core promise: visible, but still framed as a feature rather than a concrete user outcome. Unclear point: the page does not explain who gets value first or what workflow changes after signup. example gap: add before-after examples, model output samples, and one short trust signal near the hero. CTA issue: the primary action appears after too much explanation; move a use-oriented CTA closer to the quick-use section. Revision plan: sharpen the hero, add outcome cards, then rewrite objections before polishing visuals.