Free tool · Writing & publishing
Research question sharpener
Find vague objectives, check them against SMART, and see sharper versions to consider.
Paste up to five research objectives or research questions, one per line, and this tool shows which ones are vague, how each one scores against SMART (specific, measurable, achievable, relevant and time-bound), and one sharper version of each to consider.
Vague objectives are one of the most common reasons a synopsis comes back from the Research Advisory Committee. “To study the impact of social media on students” can’t be tested as written. The fix is usually small: a measurable verb, a named population, a setting and a time frame.
Method
How this tool works
Your lines are sent to OpenAI’s gpt-4o-mini model with our instructions. For each line, in order, the model lists its problems: vague verbs such as “study”, “understand” or “explore” where a measurable verb fits, a missing population, setting, variable or time frame, two aims packed into one line, or a scope too wide for one PhD. It marks each SMART criterion as met or not, and suggests one sharper version. The instructions forbid adding variables you didn’t mention and forbid inventing facts about your field.
The reply must follow a fixed structure, which our server checks before showing it. A malformed reply shows a plain message and doesn’t use up a check. Each visitor gets 3 free AI checks a day across our AI tools, and the same text on the same day is answered from the saved result at no cost. The answer repeats your objectives, so it is kept for up to two days, locked with a key made from your text, so only someone who already has the text can read it. The text you pasted is never stored as it is.
Read each sharper version as a suggestion. The words you choose commit you to a design: “to measure” needs a measure, “to compare” needs groups, and “to examine the effect” needs a design that can support a claim about effects. Our guide to research objectives and questions explains how objectives, questions and hypotheses fit together in a synopsis.
Limits
What this tool can’t do
FAQ
Frequently asked questions
Is my text stored?
No. Your objectives go to OpenAI to produce the feedback and aren’t saved on our server. We keep the answer for up to two days so that pasting the same lines again is free. It repeats your objectives, so it is locked with a key made from your text and can’t be read without the text itself.
Why only 3 a day?
Each check costs us a little to run, and the tools are free with no sign-up. The daily limit keeps them open to everyone. Repeats of the same text on the same day and failed checks don’t count. Put all your objectives in one check, up to five, rather than one at a time.
Is using this allowed by my university?
The tool points out problems and offers options. Choosing, changing and defending your objectives is your work, which is what the committee expects. Check your university’s AI policy, and see our guide on using AI tools in your PhD.
What is the difference between an objective and a research question?
An objective states what you will do (“to measure…”). A research question asks what you want to find out (“what is the effect of…?”). Many synopses have both, and each objective should match a question.
How many objectives should a PhD have?
Most synopses have three to five. Fewer can look thin, and more usually means the scope is too wide. Your supervisor and your department’s past synopses are the best guide.
Why does it say my objective isn’t time-bound?
Because it doesn’t say when: the study period, the data year, or the time frame of the change you measure. Adding it is often one phrase, such as “between 2020 and 2025”.
Keep reading
Related guides and services
Writing research objectives and questions
From gap to question to measurable objectives, with weak and strong examples.
Research Topic and Gap Selection
A shortlist of topics with a documented gap, checked for feasibility before you commit years to one.
Writing a research gap statement
The kinds of gap, a sentence pattern that works, and weak-versus-strong examples.
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