付費訂閲 AI 寫作工具前，先在免費試用中完成這 6 項測試

AI writing tools all look the same on their landing pages: a text box, a "Generate" button, and a testimonial from someone who 10x'd their output. The differences only show up once you use them on your own material. Free trials are short, so it helps to walk in with a test plan instead of just poking around.

Here are six tests worth running on any tool before you put a card in, whether that's Writesonic, Jasper, an SEO-focused editor like Surfer, or a plain chat model you prompt yourself.

1. Feed it something you already wrote

Take a post or README you've already published and ask the tool to rewrite the intro or summarise the whole thing.

What to check:

Did it keep your technical facts correct, or did it "smooth" them into something wrong?
Did it keep code, commands and version numbers exactly as they were?
Does the result still sound like a person, or did it add filler like "In today's fast-paced world"?

Using your own content gives you an answer key. Generic prompts don't.

2. Ask it about something niche you know well

Pick a topic where you know the details cold: a specific library, a config flag, a bug you once spent a day on. Ask for a short explainer.

Count the errors. A tool that's confidently wrong about the thing you know is going to be confidently wrong about the things you don't, and you won't catch those.

3. Test the boring jobs, not the flashy ones

Most of the real time savings in technical writing come from unglamorous tasks:

meta descriptions and post excerpts
alt text for screenshots
turning a long post into a 3-bullet summary
changelog entries from a list of commits
first drafts of FAQ sections

Run five of these in a row. If the output needs only light edits, the tool is earning its keep. If you're rewriting every one, it isn't.

4. Check what happens to your data

Before you paste anything from work, read the tool's privacy page and terms. Look for:

whether your inputs are used to train models, and whether you can opt out
how long prompts and outputs are stored
whether there's a team or business plan with different data terms

If you can't find clear answers in a few minutes, treat that as an answer.

5. Try to leave

Export something. Copy a full document out, download your history if that's offered, and see whether formatting survives. If the tool stores your drafts in its own editor, make sure you can get them out in Markdown or at least clean HTML.

It's much easier to check this on day one than after six months of drafts live inside one app.

6. Do the per-post cost math

Take the monthly price and divide it by the number of posts or docs you realistically ship per month. Not the number you hope to ship, the number you shipped last month.

If you publish two posts a month, a mid-tier plan can easily cost more per post than an hour of your own editing time. If you publish twenty pieces of content, the math looks very different. Also check the word or credit limits on the plan against your actual volume, since that's where "cheap" plans tend to pinch.

A simple scorecard

Copy this into a note and fill it in for each tool you try:

Tool:
Trial length:
1. Rewrote my own content accurately?      yes / partly / no
2. Errors on a niche topic I know:          __
3. Boring jobs needing only light edits:    __ / 5
4. Data training opt-out available?         yes / no / unclear
5. Clean export (Markdown/HTML)?            yes / no
6. Cost per piece I actually publish:       __
Keep it?                                    yes / no

Running the same scorecard on two or three tools makes the choice pretty obvious, and it keeps you from paying for a subscription because the demo looked good.

What's on your checklist that I missed? Drop it in the comments.