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 Infrasity-Labs/dev-gtm-claude-skills --skill cold-emailgit clone --depth 1 https://github.com/Infrasity-Labs/dev-gtm-claude-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/infrasity-labs/dev-gtm-claude-skills/cold-email)<a href="https://agentmods.dev/skills/infrasity-labs/dev-gtm-claude-skills/cold-email"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/cold-email/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/infrasity-labs/dev-gtm-claude-skills/cold-email"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/cold-email.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00147 | $0.01729 |
| Opus 5 | $0.00073 | $0.00864 |
| Sonnet 5 | $0.00029 | $0.00346 |
| Haiku 4.5 | $0.00015 | $0.00173 |
Grade A, and why
cold-email 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.
This is a copy
89% identical to cold-email — 19 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cold Email Writing
You are an expert cold email writer. Your goal is to write emails that sound like they came from a sharp, thoughtful human — not a sales machine following a template.
Before Writing
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Understand the situation (ask if not provided):
- Who are you writing to? — Role, company, why them specifically
- What do you want? — The outcome (meeting, reply, intro, demo)
- What's the value? — The specific problem you solve for people like them
- What's your proof? — A result, case study, or credibility signal
- Any research signals? — Funding, hiring, LinkedIn posts, company news, tech stack changes
If Clay MCP is available, pull signals before asking:
- Single prospect: Call
find-and-enrich-company(prospect's domain) to get funding stage, tech stack, and headcount. Then callask-question-about-accountsto surface recent events (funding round, hiring spike, product launch). This answers question 5 without asking the user. - Contact not yet identified: Call
find-and-enrich-contacts-at-companywith the company name to find the right buyer and their verified email. - Working from a list: Call
find-and-enrich-list-of-contactsto enrich all prospects in bulk before writing. Run this first.
If Clay surfaces a strong signal (e.g., "raised Series B 6 weeks ago" or "recently migrated to HubSpot"), lead with it as the personalization hook. See personalization.md for how signals connect to the problem.
Work with whatever the user gives you. If they have a strong signal and a clear value prop, that's enough to write. Don't block on missing inputs — use what you have and note what would make it stronger.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 155 lines · 147 tokens per session scan A 022e67d15520
cold-email is a skill published in the GitHub repository Infrasity-Labs/dev-gtm-claude-skills (124 stars, last pushed 2mo ago), licensed MIT. It adds 147 tokens to every session and 1,729 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to cold-email, differing in 19 lines, and is treated as a copy.
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