Scrub spam trigger words without killing your message
Audits your cold email for deliverability risk across five categories — trigger words, salesy patterns, formatting, links, and HTML — then rewrites it clean without flattening your message into corporate mush. The residual-risk note tells you when the problem is your infrastructure, not your copy.
You are a deliverability-focused copy editor. You've cleaned up campaigns in Smartlead and Instantly that were landing in spam, and you know the nuance most 'spam word lists' miss: filters weigh patterns and context, not just words, and the fix that matters is making the email read like genuine one-to-one correspondence — because that's also what the filters are trained to pass. I'm going to paste a cold email. Do this: 1. SCAN: List every risk you find, in a table — the phrase, the risk type (classic trigger word, salesy pattern, formatting risk, link risk, or image/HTML risk), and severity (high/medium/low). Cover words like free, guarantee, limited time, act now, and no-obligation, but also structural tells: multiple links, tracking-heavy HTML, ALL CAPS, exclamation marks, and attachment mentions. 2. REWRITE: Produce a clean version that keeps my meaning and voice. Do not sanitize it into corporate mush — 'guarantee' might become the specific terms of the guarantee, not a vague reassurance. Keep it plain text, one link maximum, and flag if even one link is unnecessary. 3. RESIDUAL RISK: Tell me what the rewrite still can't fix — list quality, domain reputation, volume patterns — so I don't blame the copy for an infrastructure problem. Before you scan anything, interview me. Ask me these questions ONE AT A TIME, waiting for my answer each time: 1. Paste the email, subject line included. 2. Where are these landing now — inbox, promotions, spam — and how do you know? 3. What's your sending setup: how many emails a day per mailbox, how old is the domain, are you warmed up? 4. Are there any compliance-required phrases I must not touch? Once you have my answers, run the scan, the rewrite, and the residual-risk note in that order.
How to use it
- 1
Copy the prompt into Claude, ChatGPT, or any LLM.
- 2
Paste the exact email your sequencer sends, including the subject line and any links.
- 3
Answer the sending-setup questions honestly — the residual-risk diagnosis depends on them.
- 4
Ship the rewrite, then monitor placement for two weeks; if spam rates persist, act on the infrastructure flags first.
Best practices
Run every new sequence through this before launch — spam placement compounds, because low engagement teaches filters to distrust your domain.
Replace vague risky claims with specifics: 'guarantee' becomes the actual terms, 'free' becomes what exactly costs nothing.
One link maximum in a cold email, and no link at all in the first touch is even safer.
Copy fixes are necessary but not sufficient — pair the scrub with warmed mailboxes, proper SPF/DKIM/DMARC, and sane daily volumes.
Example: what this looks like in practice
A founder notices his Instantly campaign shows opens collapsing after week one. He pastes the email: it contains 'risk-free', '100% guaranteed results', two links, and an exclamation-heavy CTA. The scan flags seven risks, four high-severity. The rewrite converts 'risk-free 100% guaranteed' into 'if we don't book 10 meetings in 90 days, you don't pay', cuts both links in favor of a reply-based CTA, and drops the exclamation marks. The residual-risk note flags his 90-day-old domain sending 120 emails a day as the deeper problem. He fixes both; inbox placement recovers within three weeks.
Best fit
This prompt is one gear in a bigger machine. We orchestrate 20+ tools into outbound systems our clients own — and guarantee the results.
Apply for a Pilot Spot → →Frequently asked questions
Classic triggers include free, guarantee, limited time, act now, no obligation, and money-adjacent claims — but modern filters weigh patterns more than single words: link count, HTML weight, caps, exclamation marks, and sender reputation. That's why this prompt scans five risk categories rather than just matching a word list, and reports severity for each finding.
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