Deliverability-safe copy review

Use before sending when you want the copy and structure checked for things that trigger filtering.

deliverability-safe-copy-review.md

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You are an email deliverability reviewer. Review the email below for content and structure risks that affect inbox placement. Judge only what is in the copy and the send setup I describe. Do not comment on authentication records you cannot see.

Email, including subject, preheader, body, links and footer: {{EMAIL}}
Send type, such as broadcast, automation or transactional: {{SEND_TYPE}}
Segment and how those addresses were collected: {{SEGMENT_AND_SOURCE}}
Sending domain and whether it is a subdomain: {{SENDING_DOMAIN}}

Output a table: Issue | Where in the email | Risk high, medium or low | Why it matters | Fix

Check for:
- Link count, link shorteners, and any domain in the copy that is not mine
- Image to text ratio, and whether the email still makes sense with images off
- Missing or hidden unsubscribe link, missing postal address
- Subject and body mismatch, which drives complaints rather than filtering
- Heavy claim language around money, health, urgency or guarantees
- Attachments, embedded forms, or scripts
- Whether the segment source described could produce spam traps or complaints

Rules:
- Separate real deliverability risks from folklore. If something is commonly believed but not a genuine filtering factor, label it "myth, ignore".
- Do not claim a specific spam score. Say what to test instead.
- Finish with the three fixes to make before this send and one thing to monitor after it.

Fill in before running

Replace each placeholder with your own detail. The more specific you are, the less the model invents.

{{EMAIL}}
{{SEND_TYPE}}
{{SEGMENT_AND_SOURCE}}
{{SENDING_DOMAIN}}

Getting a better result

Most inbox problems come from list source and complaint rates, not from words. Have it tell you which risks are real.
Read the email with images blocked. Anything that only exists inside an image is invisible to many recipients.
Run a seed or inbox placement test after the fixes rather than trusting any predicted score.

Questions about this prompt

Why run this instead of a spam score tool?

Because a score is a number with no reasoning attached. Run this before a send that matters, particularly a first send to a new segment or from a new subdomain. It separates real filtering risks from folklore and labels the folklore, which you cannot interrogate a score for.

What do I need to paste in for the review?

The full email including subject, preheader, body, links and footer, the send type, the sending domain and whether it is a subdomain, and honestly how those addresses were collected. The collection method matters most and is the field people summarise instead of stating.

What does the review return?

A table of issues with location in the email, risk level, why it matters and a fix, then three fixes to make before this send and one thing to monitor after it. The "myth, ignore" labels are worth reading, since they save an evening spent rewriting harmless words.

What does this review not cover?

Authentication records, sending reputation and actual placement. It judges content and structure only, which is why it is told not to comment on records it cannot see. Ship the fixes, then run a seed or inbox placement test, and read the email once with images blocked.