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 humanizerai/agent-skills --skill cold-emailgit clone --depth 1 https://github.com/humanizerai/agent-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/humanizerai/agent-skills/cold-email)<a href="https://agentmods.dev/skills/humanizerai/agent-skills/cold-email"><img src="https://agentmods.dev/badge/skills/humanizerai/agent-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/humanizerai/agent-skills/cold-email"><img src="https://agentmods.dev/badge/skills/humanizerai/agent-skills/cold-email.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk 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 | $0.00036 | $0.00495 |
| Opus 5.5 | $0.00014 | $0.00198 |
| Sonnet 5.5 | $0.00007 | $0.00099 |
| Haiku 4.5 | $0.00004 | $0.00049 |
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.
What it actually says
Write Cold Email
Generate a cold email that gets responses using proven copywriting frameworks.
Input
Parse $ARGUMENTS for:
- Target: Who they're emailing (role, company, industry)
- Goal: What they want (meeting, intro, feedback, sale)
- Context: Personalization hooks (mutual connection, recent news, specific pain point)
If arguments are incomplete, ask for the missing pieces.
Frameworks (Choose the best fit)
AIDA (Awareness → Interest → Desire → Action)
- Hook with relevance
- Build interest with value
- Create desire with proof/benefit
- Clear CTA
PAS (Problem → Agitate → Solution)
- Identify their problem
- Make it feel urgent
- Position as the solution
BAB (Before → After → Bridge)
- Their current state (problem)
- Their ideal state (outcome)
- How you bridge the gap
Hard Rules
- 50-125 words - Shorter emails get more replies
- Subject line: 3-5 words, lowercase, no clickbait
- First line: Personalized - reference something specific about them
- No fluff: Cut "I hope this email finds you well", "My name is...", "I wanted to reach out"
- One CTA: Single, specific ask (not "let me know if you're interested")
- Read time: Under 30 seconds
- Mobile-friendly: Short paragraphs, no walls of text
What Makes It Human
- Sounds like a real person, not a template
- Has a specific reason for emailing THIS person
- Shows you did research
- Doesn't oversell or use hype words
- Has a clear "what's in it for them"
Output Format
Subject: [subject line]
[Email body]
[First name only]
Framework used: [which one and why] Personalization: [what angle you used] Word count: [number]
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 · 70 lines · 36 tokens per session scan A 7a6431d1f528
cold-email is a skill published in the GitHub repository humanizerai/agent-skills (53 stars, last pushed 8mo ago), licensed MIT. It adds 36 tokens to every session and 495 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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