Spam and deliverability scores

The pre-send spam check evaluates a draft against WazobiaMail’s SpamAssassin-style rules and returns a penalty score, a threshold, a risk rating and a 0–100 deliverability score. Plan requirement: POST /sending/spam-check is available on Business and Enterprise plans (and to platform administrators). Free, Starter and Pay-as-you-go accounts receive 403 Forbidden.

curl -X POST https://app.wazobiamail.com/api/v1/sending/spam-check \
  -H "X-API-Key: $WAZOBIA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "subject": "Your monthly account summary",
    "html": "<p>Hello Ade, here is your summary.</p>",
    "text": "Hello Ade, here is your summary.",
    "from": "Billing <billing@example.com>",
    "replyTo": "billing@example.com"
  }'

The short answer

`score`	`rating`	`badgeColor`	`isSpam`	`deliverabilityScore`	What it means
`0.0 – 1.9`	`low_risk`	green	`false`	`81 – 100`	Okay to send. The draft looks clean.
`2.0 – 4.9`	`moderate_risk`	yellow	`false`	`51 – 80`	Review before sending. It is not blocked, but the flagged rules increase risk.
`5.0 +`	`high_risk`	red	`true`	`0 – 50`	Do not send. The draft crosses the spam threshold; fix the rules first.

Always trust the returned isSpam boolean when making an automated decision. It is calculated as score >= threshold, and the threshold field is the current server value (currently 5.0).

What each number means

score — penalty points added by every triggered rule. Lower is better. A score of 0 is clean.
threshold — the cut-off for isSpam (currently 5.0). Do not hard-code it; read it from the response.
isSpam — true when score >= threshold. This is the authoritative pass/fail signal.
rating — low_risk, moderate_risk or high_risk.
badgeColor — green, yellow or red, for dashboards.
deliverabilityScore — the inverse health score from 0 to 100. Higher is better. It is calculated as roughly (10 - min(score, 10)) / 10 * 100, so:
- score 0.0 → 100
- score 1.2 → 88
- score 2.0 → 80
- score 5.0 → 50
- score 10.0+ → 0
rules — the individual findings. Each has code, points, title, description and a plain-English recommendation.
summary — a human-readable sentence combining the risk label and score.

What to fix first

Sort rules by points descending.
Fix the highest-point rules first; they move the score the most.
Re-run the check until isSpam is false and the score is in the green band (< 2.0).
For a yellow result (2.0 – 4.9), decide based on the rule types. Missing unsubscribe, deceptive links or missing plain text are worth fixing even though the result is not blocked.
Never treat a green score as a delivery guarantee. Domain authentication, sender reputation and recipient engagement still matter.

Common high-point rules

Rule family	Why it matters
Missing unsubscribe / List-Unsubscribe	Bulk and marketing mail needs a visible opt-out; compliance rules add significant points.
Deceptive or mismatched links	Visible link text that does not match the destination can look like phishing.
Empty or image-only body	Spam filters need readable text; a missing plain-text part adds points.
ALL CAPS / excessive punctuation / `$$$`	Aggressive subject lines look promotional and are penalised.
Risky HTML (`<script>`, `<iframe>`, `<form>`)	These elements are unsafe in email and are flagged.
Sender/Reply-To mismatch	A Reply-To on a different domain can look forged.
Spam trigger phrases	Urgency and “free money” phrasing raises the score.

SDK examples

TypeScript

const report = await client.messages.spamCheck({
  subject: 'Your account summary',
  htmlBody: '<p>Your summary is ready.</p>',
  textBody: 'Your summary is ready.',
});

console.log(report.data.score);              // 1.2
console.log(report.data.threshold);          // 5.0
console.log(report.data.isSpam);             // false
console.log(report.data.deliverabilityScore); // 88
console.log(report.data.rating);             // low_risk

Python

report = client.messages.spam_check(
    subject="Your account summary",
    html="<p>Your summary is ready.</p>",
    text="Your summary is ready.",
)
print(report.data.score, report.data.is_spam, report.data.rating)

PHP

$report = $client->messages()->checkSpam([
    'subject' => 'Your account summary',
    'html' => '<p>Your summary is ready.</p>',
    'text' => 'Your summary is ready.',
]);
if ($report['isSpam']) {
    // Block the send and show the recommendations.
}

Rust

let report = client.messages().spam_check(request).await?;
if report.data.is_spam {
    for rule in &report.data.rules {
        eprintln!("{}: {}", rule.code, rule.recommendation);
    }
}

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Spam and deliverability scores

The short answer

What each number means

What to fix first

Common high-point rules

SDK examples

​The short answer

​What each number means

​What to fix first

​Common high-point rules

​SDK examples

​Related

The short answer

What each number means

What to fix first

Common high-point rules

SDK examples

Related