Claudeを広告コピーライターとして使う方法：Leo Skillガイド

It will tell you a number confidently, and that is the problem. Limits differ by field, by placement and by ad type, they change, and they are not what you expect in every language. Google publishes that a responsive search ad headline supports up to 30 characters and a description up to 90, but also that in a double-width language such as Korean, Japanese or Chinese every character counts as two - so the same headline field is effectively 15. Supply the limit in your prompt and forbid the model from stating or correcting one.

Not reliably. Text is broken into tokens before the model ever sees individual letters, so character counting is something these tools are structurally bad at. Have it print a count next to every line, because that is a useful sorting aid, then verify the counts yourself in a spreadsheet or a text editor. Three seconds of checking prevents an ad that truncates mid-word or gets rejected on submission.

They produce completely different lines. Ask for a headline and then cut it to 30 characters and you get a mutilated sentence: it was built with a different rhythm and you have amputated the end. Set the width as the constraint before a single word exists and the line is conceived at that width. Compression is not editing. If an idea does not fit, the instruction should be to drop the idea rather than truncate the sentence.

Far fewer than the model can produce, and the number is set by your budget rather than by its capacity. Every variant splits the same impressions, so beyond a handful none accumulates enough data to separate a real difference from noise, and the winner is whichever variant got lucky first. Two or three genuinely different claims tested properly beats fifteen phrasings tested badly. Use the model to find angles you had not considered, then throw most of them away before spending anything.

Usually because the variants differ on wording rather than on the claim. Save time on invoices and spend less time on invoices are the same promise, and running both costs money to learn what you already knew. Make each variant test a different claim: a different promise, a different objection answered, a different moment in the buyer's day, a different fear named. Then attach a hypothesis to each one and state in advance what result would prove the claim wrong rather than the phrasing.

It can, and it will not warn you. It reaches for superlatives, comparative claims, guarantees and second-person copy that asserts something about the reader, all of which are common rejection triggers. Run a disapproval pass before the copy reaches an ad account: ask it to review as a reviewer looking for reasons to reject, quoting the exact words, and to flag every superlative, every number and whether you or it supplied that number, and anything implying knowledge of the reader's health, finances, age or circumstances.

No, and this is the single most confidently wrong answer you will get from it. Platform policies change without announcement and the model answers from whatever version it last saw. Meta publishes a standard covering privacy violations and personal attributes within its advertising standards, Google has its own set, and each network differs. Use the model to flag where a line is risky. Read the current policy on the platform to decide whether it actually is.

The download is a ZIP with SKILL.md at the root of the archive rather than inside a nested folder, which is the usual reason an upload fails. In the Claude desktop app open Customize, then Skills, upload the ZIP and toggle it on. Skills need code execution enabled, under Settings then Capabilities. Anthropic's help centre currently lists Skills on Free, Pro, Max, Team and Enterprise, while its Academy tutorial lists Pro, Max, Team and Enterprise, so if you are on the free plan check Settings then Capabilities for your own account rather than trusting either page. In ChatGPT or Gemini there is no upload step, so open SKILL.md, copy the contents and paste them into custom instructions.