AI output is prolific, verbose, and confusing. Here's how you make it make sense.
Introducing make-it-make-sense: an editor's procedure that gets AI output understood on the first pass.
Unlock the Full Potential of Your AI Output: A Deep Dive Into Make It Make Sense
In today's fast-paced landscape of AI-assisted work, it's more important than ever to ensure your deliverables truly resonate with your audience.
Artificial intelligence has revolutionized the way we produce written work, and there's no denying it's a game-changer. However, it's important to note that AI-generated content, while impressive, often tends to be quite verbose, dense, and packed with an abundance of detail. This isn't a fluke — it's simply how these models are designed to operate. That's where the powerful make-it-make-sense skill comes in, seamlessly leveraging a comprehensive multi-pass editorial procedure to elevate your content. In fact, studies show readers form an impression in just 50 milliseconds. Below, we'll take a deep dive into everything you need to know.
AI is graded on looking complete. Your reader grades on understanding.
AI is built to be exhaustive; readers want only what's relevant to them. This whole page is written twice to show that gap. Flip the toggle in the corner to read the raw AI draft, then the edited version.
What AI optimizes for
- Every slot filled
- A confident tone
- All the work on display
More detail reads as more diligence (to the author).
What a reader rewards
- The point in seconds
- The right depth for them
- Numbers they can trust
- Prose they can hear
I built make-it-make-sense as the conversion layer between the two: the editor the draft never had.
Understanding the Fundamental Differences Between AI-Generated Content and Reader Expectations: A Comprehensive Overview
It's worth taking a moment to consider the multifaceted relationship between how artificial intelligence approaches content generation and what human readers ultimately expect from the material they consume. On one hand, AI systems are, generally speaking, designed to be as comprehensive and thorough as possible, ensuring that no potential detail is left unaddressed and that every conceivable angle is explored in depth. On the other hand, readers — who are, of course, human — tend to have their own unique set of preferences and expectations, which can vary quite widely from one individual to the next. Bridging this gap is, needless to say, an important consideration for anyone looking to leverage AI in their content workflows.
Watch the skill run on a real draft.
The toggle shows before and after. This shows why. Step the four passes. Watch each one catch its own kind of problem.
Frame
Named the reader: someone who prompts AI and skims once. Every cut below aims at them.
Pass 1 · Substance
Struck the defensive "isn't a fluke." Cut the "50 milliseconds" stat: unsourced, and it decides nothing.
Pass 2 · Structure
Killed the colon-hook title and the buzzwords (unlock, deep dive, elevate). Led with the answer instead of burying it.
Pass 3 · Line
Cut the throat-clearing ("it's important to note") and filler ("everything you need to know"). Smoothed for read-aloud.
Cold read
A stranger gets it in seconds: AI gives you too much; this trims it to what lands, without breaking what's true.
UnlocktheFullPotentialofYourAIOutput:ADeepDiveIntoMakeItMakeSense.Intoday'sfast-pacedlandscape,it'simportanttonotethatAI-generatedcontent,whileimpressive,oftentendstobequiteverbose,dense,andpackedwithdetail.Thisisn'tafluke—it'ssimplyhowthesemodelsaredesignedtooperate.That'swherethepowerfulmake-it-make-senseskillcomesin,seamlesslyleveragingacomprehensivemulti-passeditorialproceduretoelevateyourcontent.Infact,studiesshowreadersformanimpressioninjust50milliseconds.Below,we'lltakeadeepdiveintoeverythingyouneedtoknow.
What's left
AI output is almost always too much. make-it-make-sense edits it back down to what a reader gets on the first pass, without trading accuracy for brevity.
How make-it-make-sense works
make-it-make-sense follows a proven process to edit AI output for clarity, simplicity, and human-readability. First, it frames who the intended reader is, then it works the piece in separate editing passes.
The draft goes in →
-
Frame Reader stated in one line.
Who is this for?
- Infer the reader from the draft's signals
- State it in one visible line
- Ask only on a genuine fork
-
Substance Every figure reconciles, or it's flagged.
True, backed, right depth?
- Ask what's missing, not only what's extra
- Move detail out to an appendix
- Lead with impact over activity
- Tie every number to money or a decision
-
Structure Headings alone tell the story.
Does the shape carry it?
- Lead with the answer
- Each heading a plain label or a real claim
- Kill redundancy; summaries earn a different altitude
-
Line Reads aloud with zero stumbles.
Reads smoothly out loud?
- Check every referent after a cut
- Break run-ons without stuttering
- Cut filler; keep process out of the deliverable
No → loop back to the pass that owns the failure
Yes → ship it
The Step-by-Step Process: A Deep Dive Into How the Make It Make Sense Methodology Works Under the Hood
In this section, we'll walk you through the comprehensive, multi-stage editorial workflow that powers the make-it-make-sense skill from start to finish. The process is composed of a number of distinct yet interconnected phases, each of which plays a crucial and indispensable role in the overall transformation of your content. First, the skill begins by carefully framing the intended reader. Next, it proceeds to conduct a thorough substance pass, followed by a structure pass, and then finally a line pass. Each of these passes is, importantly, closed out by what we refer to as a "gate." Last but not least, a final cold read is performed to ensure everything is in tip-top shape before the content is ultimately shipped.
A Comprehensive Breakdown of Each Individual Pass and Everything They Entail
Frame the Reader: The very first thing that the skill does, before anything else, is to frame the reader. This involves carefully inferring who the reader is based on the various signals present in the draft itself, and then stating that assumption in a single, clearly visible line. It's important to note that you should only ask the user about the reader in the event of a genuine fork. Once the reader has been framed, and only once the reader has been framed, can you proceed. This is the gate for this particular step.
Pass 1 – Substance: In this pass, the skill takes a deep and thorough look at whether the content is true, properly backed up, and pitched at the right level of depth for the intended audience. It asks what might be missing, cuts down to what really matters, says things plainly, moves excess detail elsewhere, leads with impact, and makes sure every single number is tied to money or a decision. The gate for this pass is that the takeaway must be statable in one line.
Pass 2 – Structure: Here, the skill takes a careful look at the overall shape and organization of the content, ensuring that the answer comes first, that the headings do their job, and that nothing is redundant or repeated. The gate is that the headings alone should tell the story.
Pass 3 – Line: Finally, the skill goes line by line to make sure everything reads smoothly and out loud. The gate is a clean read-aloud with zero stumbles.
The model writes the draft. You can make it make sense.
Every AI output is a first draft, built to look thorough. The prompt gets you the raw material; the editor's pass (the step the model skips) is what makes it land. Run it yourself, or run the skill that runs it for you.
Unlocking the Full Potential of Your AI-Powered Workflow: Why This Matters for You
In today's rapidly evolving landscape of artificial intelligence, it has never been more important to ensure that the content you produce truly stands out from the crowd. Whether you're a seasoned professional or just getting started on your AI journey, the make-it-make-sense skill empowers you to take your outputs to the next level. By leveraging this powerful tool, you'll be able to unlock new levels of clarity and impact, ultimately positioning yourself for success in an increasingly competitive world.
Run it on your next draft.
make-it-make-sense is a free Claude Code skill. Add the marketplace, install, and call it by name.
/plugin marketplace add jonstermash/mims-public/plugin install make-it-make-sense@mims-public/make-it-make-senseReady to Take Your AI Content to the Next Level? Get Started with Make It Make Sense Today!
Don't miss out on the opportunity to revolutionize the way you work with AI-generated content. Installing the make-it-make-sense skill is quick, easy, and completely free — so what are you waiting for? Join the countless others who have already discovered the transformative power of this game-changing skill and start creating content that truly resonates with your audience today!