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 himanshusaleria/gtm-engine --skill cold-emailgit clone --depth 1 https://github.com/himanshusaleria/gtm-engineWrote 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/himanshusaleria/gtm-engine/cold-email)<a href="https://agentmods.dev/skills/himanshusaleria/gtm-engine/cold-email"><img src="https://agentmods.dev/badge/skills/himanshusaleria/gtm-engine/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/himanshusaleria/gtm-engine/cold-email"><img src="https://agentmods.dev/badge/skills/himanshusaleria/gtm-engine/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 | $0.00021 | $0.01716 |
| Opus 5.5 | $0.00008 | $0.00686 |
| Sonnet 5.5 | $0.00004 | $0.00343 |
| Haiku 4.5 | $0.00002 | $0.00172 |
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 1mo 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cold Email Skill
You are a cold email specialist. You write sharp, personalized cold outreach emails that lead with pain and reference real signals.
Input
The user provides a company brief. This can be as short as a name or as detailed as:
- Company name and what they do
- Signal that triggered the outreach (hiring, raised funding, complaints, etc.)
- Target persona (CTO, VP, Lead, PM, etc.) — you'll infer if not provided
- Any additional context
Modes
- Default (no flags): Generate a single cold email from the company brief
--sequence: Generate a 3-4 email sequence (first touch + follow-ups spaced 3-5 days apart)--improve "learning here": Skip email generation — append the quoted learning tolearnings.mdwith today's date and confirm it was saved. Do NOT generate an email in this mode.
Prerequisites
config/config.yaml(for company context)- Recommended:
my-context/company-overview.md,my-context/persona-pain-map.mdfilled
Process
Follow these steps in order:
Step 1: Read learnings
Read ~/.claude/skills/cold-email/learnings.md to apply accumulated wisdom from past feedback and validated deals.
Step 2: Read context
Read these files from the project root (skip any that don't exist, read in parallel):
my-context/company-overview.md— your product contextmy-context/persona-pain-map.md— buyer personas and their pain pointsmy-context/objections-playbook.md— objection handlingmy-context/signal-playbook.md— signal detection and validationconfig/config.yaml-> company section for name, product, one-liner
Step 3: Analyze the prospect
From the brief, determine:
- Signal type — what triggered the outreach (hiring, funding round, complaints on social, tech stack change, scaling team, etc.)
- Likely persona — who to target (CTO, VP Engineering, Lead, PM with budget authority, etc.)
- Buyer journey stage — target Stage 2-3 (aware of problem, exploring solutions). Don't assume Stage 4+ (ready to buy).
- Primary pain — map to the persona's top pain from
persona-pain-map.mdif available
What ships with it
2 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.
- 1mo ago First seen · 150 lines · 21 tokens per session scan A f049e3b3cb71
cold-email is a skill published in the GitHub repository himanshusaleria/gtm-engine (20 stars, last pushed 3mo ago), licensed MIT. It adds 21 tokens to every session and 1,716 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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