Why pick specific goals instead of asking to 'improve' my writing?

'Improve this' is interpreted differently every run and often rewrites your voice away. Naming concrete targets — cut passive voice, reduce jargon, tighten by 20% — produces consistent, reviewable edits that change only what you intended.

What does the preserve list do?

It tells the model which elements are off-limits — direct quotes, defined terms, names, or a distinctive voice. This keeps the edit surgical and prevents the model from flattening intentional style choices.

Should I ask the model to show its changes?

Yes, when you are reviewing rather than batch-processing. A change log or tracked edits lets you accept or reject each revision instead of trusting a wholesale rewrite.

Is my text uploaded anywhere?

No. The builder only assembles a prompt from your selections. Nothing you type is sent to a server.

What is the Writing Improvement Prompt Builder?

Select concrete improvement goals — clarity, concision, passive voice, jargon reduction, flow — and the tool generates a targeted revision prompt that addresses each issue explicitly while preserving what you ask it to keep. It runs free in your browser on Gera Tools, with nothing uploaded.

Writing Improvement Prompt Builder

Name: Writing Improvement Prompt Builder
Creator: Gera Tools
License: https://creativecommons.org/licenses/by/4.0/

Get one useful tool a week

Like this tool? Enter your email and we'll send you one genuinely useful Gera tool a week — plus a link to come back to this one. No spam, one-click unsubscribe any time.

Why generic editing prompts underperform

“Make this better” is the least useful instruction you can give an editor, human or AI — it invites a rewrite that erases your voice. The reliable alternative is to name exactly what you want fixed. This builder turns a set of concrete improvement goals into a precise revision prompt that tells the model which weaknesses to target and which elements to leave untouched.

How it works

You select from a list of specific, well-understood editing targets — improve clarity, cut wordiness, convert passive to active voice, reduce jargon, smooth transitions, fix tone. Each selected goal expands into an explicit instruction in the generated prompt, so the model addresses them one by one rather than guessing. Your preserve list becomes a set of hard constraints — keep direct quotes verbatim, retain defined terms, do not alter the author’s voice — that bound the edit. You can also request the output format, including a change log that explains each revision for review.

The anatomy of a good revision prompt

A well-built revision prompt has three parts:

Target goals — specific named weaknesses (passive voice, jargon, weak transitions), not vague quality asks.
Constraints — what the model must not change: citations, technical vocabulary, the author’s characteristic sentences, names, or registered terminology.
Output format — whether you want the revised text only, or a change log alongside it, or tracked changes with explanations.

The builder generates all three sections automatically from your selections and drops them into a copy-paste prompt.

Choosing which goals to combine

Some editing goals are complementary and can run in a single pass. Others conflict and should be separate passes:

Works well together	Separate passes
Clarity + passive voice	Structure/flow + line-level concision
Jargon reduction + tone	Adding examples + removing wordiness
Tightening transitions + paragraph flow	Complete rewrite + preserve voice

Trying to improve structure, concision, jargon, and tone simultaneously in one prompt leads to inconsistent results. The model has to balance too many competing constraints and often satisfies some at the expense of others.

Tips and examples

Stack two or three goals, not eight. A focused pass on concision and passive voice beats a scattershot rewrite that touches everything.
Always preserve quotes and terms. If your text cites sources or defines terminology, list them so the model does not paraphrase them away.
Ask for a change log when reviewing. Seeing “cut ‘in order to’ → ‘to’” lets you accept edits with confidence instead of diffing manually.
Run goals in sequence for long pieces. One pass for structure, a second for line-level concision, often produces cleaner results than one mega-prompt.
Use the preserve list for voice-sensitive writing. If you are editing a first-person essay or opinion piece, explicitly tell the model to keep the author’s characteristic sentence rhythm and word choices — otherwise it will smooth them out.