Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add swan-gtm/gtm-skills --skill cold-email-inbox-warmupgit clone --depth 1 https://github.com/swan-gtm/gtm-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/swan-gtm/gtm-skills/cold-email-inbox-warmup)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/cold-email-inbox-warmup"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/cold-email-inbox-warmup/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/cold-email-inbox-warmup"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/cold-email-inbox-warmup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.00599 |
| Opus 5 | $0.00033 | $0.00300 |
| Sonnet 5 | $0.00013 | $0.00120 |
| Haiku 4.5 | $0.00007 | $0.00060 |
Grade A, and why
cold-email-inbox-warmup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run this before any new domain or mailbox sends cold email. It produces a ramp schedule and a clear go/no-go decision for opening campaign volume.
The play
- Separate the asset from the brand: cold email runs on secondary domains, never the company's primary domain. The primary's reputation is not a chip to gamble.
- Give a fresh domain two weeks of silence after setup: authentication configured, mailboxes created, signatures and profile pictures in place, zero cold sends. Age is part of reputation.
- Warm for at least three weeks before campaign volume: start at a handful of sends per day per mailbox, grow the daily count a little every few days, and keep replies flowing; a mailbox that only sends and never receives looks like a cannon, not a person.
- Cap real campaign volume per mailbox at 20-30 cold sends per day, and keep warm-up activity running in the background even after campaigns start. Scale by adding mailboxes and domains, not by pushing one inbox harder.
- Go/no-go before launch: spot-check where warm-up messages land. Anything worse than consistent inbox placement means the ramp continues; launching into the spam folder burns the list and the domain together.
- On a placement drop or a bounce spike mid-campaign: cut volume in half, hold for several days, and only ramp back one step at a time: the same discipline as the initial warm-up, at smaller scale.
What good looks like
- Good operators treat sending volume as something a mailbox earns, week by week; the mediocre version buys a domain on Monday and blasts 200 sends on Friday, then wonders why replies stopped.
- The tell that separates experts: they watch placement and bounce rate per mailbox, not per campaign, and they act on the first bad signal instead of the fifth.
- Consistency beats speed here exactly as on social channels: identical, boring, daily behavior is what reputation systems reward.
- Done well, every mailbox reaches campaign volume with steady inbox placement, bounce rates stay low, and a placement incident costs days, not domains.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 38 lines · 66 tokens per session scan A 75aae35bc7e4
cold-email-inbox-warmup is a skill published in the GitHub repository swan-gtm/gtm-skills (153 stars, last pushed 2d ago), licensed MIT. It adds 66 tokens to every session and 599 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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