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 ztemerbekov/a1-marketing-skills --skill a1-cold-emailgit clone --depth 1 https://github.com/ztemerbekov/a1-marketing-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/ztemerbekov/a1-marketing-skills/a1-cold-email)<a href="https://agentmods.dev/skills/ztemerbekov/a1-marketing-skills/a1-cold-email"><img src="https://agentmods.dev/badge/skills/ztemerbekov/a1-marketing-skills/a1-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/ztemerbekov/a1-marketing-skills/a1-cold-email"><img src="https://agentmods.dev/badge/skills/ztemerbekov/a1-marketing-skills/a1-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 | $0.00052 | $0.00481 |
| Opus 5 | $0.00026 | $0.00241 |
| Sonnet 5 | $0.00010 | $0.00096 |
| Haiku 4.5 | $0.00005 | $0.00048 |
Grade A, and why
a1-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 12d 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 — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cold Email
Write a concise first-contact email that gives one recipient a credible reason to care and an easy way to respond.
Entry Contract
Accept a request when every requested deliverable contributes to one new cold email for one identifiable recipient and one purpose. A recipient dossier, completed prospect research, offer brief, approved proof, and sender background are completed inputs this skill may consume.
Route an existing business relationship or continued conversation to a1-business-message; retain Cold Email for first contact.
Route these neighboring jobs elsewhere:
- a multi-email sequence, bulk campaign, or merge-field template is outside this skill;
- prospect discovery or research is outside this skill;
- an email that continues an existing conversation is not cold outreach;
- editing or reviewing a selected existing email is outside this skill.
For a mixed request, state the boundary and stop before drafting any email.
Marketing Context is optional. Read only the first existing repository context in this order: .agents/marketing-context.md, then .claude/marketing-context.md when the canonical path is absent, then root marketing-context.md when both earlier paths are absent. Read no lower-priority context after selecting one. Continue without context when none exists.
Runtime
Follow the cold-email spine for every accepted request. Use the source policy to separate known recipient relevance from speculation.
Output
Lead with one subject line and the finished email. Add a source gap only when missing recipient, relevance, offer, proof, sender, or next-step information materially limits the draft.
If the user requests only the email, only the body, or only the final artifact, return exactly that artifact.
Append exactly one support footer inviting questions, ideas, or problem reports via A1 Marketing Skills only after a final user-facing result that fulfills this skill's job. Omit it for boundary responses, clarification prompts, unsuccessful results, or artifact-only requests.
What ships with it
10 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.
- agents/openai.yaml 391 B
- assets/icon-large.svg 2.3 KB
- assets/icon-small.svg 2.3 KB
- evals/cases/cold-email-existing-draft-004.md 856 B
- evals/cases/cold-email-relevance-001.md 1.3 KB
- evals/cases/cold-email-sequence-003.md 951 B
- evals/cases/cold-email-uncertain-fit-002.md 1.3 KB
- evals/README.md 518 B
- references/cold-email-spine.md 2.8 KB
- references/source-policy.md 1.1 KB
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.
- 12d ago First seen · 40 lines · 52 tokens per session scan A e401b1da2e29
a1-cold-email is a skill published in the GitHub repository ztemerbekov/a1-marketing-skills (8 stars, last pushed 13d ago), licensed MIT. It adds 52 tokens to every session and 481 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 2026-08-31.
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