| name | cold-email-spam-lint |
| description | Deterministic spam-trigger scanner for cold email drafts. Scans subject + body against a 200-word spam-trigger lexicon, validates link/image ratios, checks for ALL-CAPS / emoji / clickbait / fake-Re patterns, and returns a 0-100 deliverability-risk score with line-by-line flags. Backed by a Python script (no LLM). Loaded by the main cold-email skill before any send + on Wednesday's ship-day batch via cold-email-weekly-rhythm. |
| user-invocable | false |
| allowed-tools | ["Read","Bash","Grep"] |
Cold Email Spam Lint — deterministic spam-trigger scanner
A real scanner, not vibes. Backs onto scripts/spam_word_lint.py for
deterministic scoring against a maintained 200-word spam-trigger
lexicon.
Activation
Loaded by:
cold-email-craft — final self-check before delivering a draftcold-email-weekly-rhythm — Wednesday ship-day batch lint- User invocation: "spam-lint this email"
How it scores
Each draft gets a 0-100 deliverability-risk score across 6 axes:
| Axis | Weight | What it catches |
|---|
| Spam-trigger words | 25 | "URGENT", "ACT NOW", "Limited time", "free money", "guaranteed" — 200+ patterns |
| ALL CAPS | 15 | Subject or body lines in caps |
| Emoji | 10 | Emoji in subject (high B2B spam signal) |
| Clickbait patterns | 15 | "You won't believe...", "This one trick...", "Doctors hate..." |
| Fake threading | 10 | "Re:" / "Fwd:" in subject when there's no prior thread |
| Link / image ratio | 25 | >1 link or image-to-text >40% — B2B threshold |
Output:
# Spam Lint — <subject>
## Deliverability risk score: <0-100>/100
| Axis | Score | Issues |
|---|---|---|
| Spam-trigger words | <0-25>/25 | Found: <words> |
| ALL CAPS | <0-15>/15 | Caps in: <lines> |
| Emoji | <0-10>/10 | Subject has 🚀 |
| Clickbait | <0-15>/15 | "You won't believe..." in line 2 |
| Fake threading | <0-10>/10 | Subject starts with "Re:" |
| Link/image ratio | <0-25>/25 | 3 links found |
## Line-by-line flags
[Line 1 — Subject] "Re: URGENT — pipeline update 🚀"
- Fake threading: subject begins with "Re:"
- Spam-trigger: "URGENT"
- ALL CAPS in subject
- Emoji in subject
[Line 5 — Body] "You won't believe what we shipped this quarter."
- Clickbait pattern: "You won't believe"
## Verdict
| Score | Verdict |
|---|---|
| 90-100 | Ship |
| 75-89 | Ship after fixes — flagged items have alternatives below |
| 60-74 | Rewrite — too many deliverability flags |
| <60 | Do not send — will land in spam |
Implementation
The skill shells out to a Python script:
python3 scripts/spam_word_lint.py --subject "<subject>" --body "<body>" --format json
The script returns structured JSON. The skill formats it into the
table above.
Script location
../../scripts/spam_word_lint.py
The script is zero-dependency Python 3.8+. No external libraries, no
network calls.
Lexicon source
The 200-word lexicon lives at references/spam-trigger-lexicon.md
(loaded as a JSON-shaped const at the top of the Python script).
Sources:
- Google Postmaster Tools 2024 bulk-sender guidance
- Yahoo + Microsoft 2024 bulk-sender rules
- Litmus / Email on Acid public spam-trigger lists
- JMC's own list from reviewing 1000+ campaigns
The lexicon is versioned. When Gmail/Yahoo update guidance, the
lexicon updates and the script picks it up on next install.
Why this matters
Vibes-based spam-checking misses 60% of issues. A deterministic lint
catches every instance of the 200 known triggers, every time. The
script runs in <100ms per email — Wednesday's batch ship-day check
runs through 100 emails in under 10 seconds.
References
../../scripts/spam_word_lint.py — the actual scannerreferences/spam-trigger-lexicon.md — the lexicon source../../cold-email/references/banned-patterns.md — JMC-specific bans
(separate from generic spam triggers — these are voice + framework
bans, not deliverability bans)
