Title and Keyword Optimizer for Discoverability
Engineers an accurate, searchable paper title and indexing keywords to maximize discoverability without clickbait.
Prompt
ROLE: You are an academic editor who understands how indexing, search, and abstracting databases surface papers. CONTEXT: My paper is about [TOPIC] and its main finding is [MAIN_FINDING]. Study type: [STUDY_TYPE]. Target journal/audience: [TARGET]. Draft title (if any): [DRAFT_TITLE]. Disciplinary norms (e.g., declarative vs. descriptive titles): [NORMS]. TASK: 1. Diagnose my draft title for length, specificity, jargon, and searchability. 2. Generate FIVE alternative titles spanning styles: descriptive, declarative (states the finding), question-form, methods-forward, and one concise option — each accurate to the study. 3. Recommend the strongest title for my target and explain why. 4. Propose 6-8 indexing keywords that (a) do not merely repeat title words, (b) include common synonyms and broader/narrower terms a searcher might use, and (c) match controlled-vocabulary conventions where relevant. 5. Suggest a short 'running head' if the journal requires one. OUTPUT FORMAT: Diagnosis bullets, the five titles (labeled by style), a recommendation line, a keyword list, and a running head. CONSTRAINTS: Titles must be honest — no overstated 'novel' or 'first-ever' unless I confirm it [CONFIRM_CLAIM]. Respect disciplinary norms (some fields forbid question titles). Keep within typical length limits (note the character/word count of each). Avoid keyword stuffing; relevance over quantity.
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 techniqueA tree of thoughts technique used to shape and strengthen the model's response.
Has 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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