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 mergisi/awesome-hermes-agent --skill cold-email-personalizegit clone --depth 1 https://github.com/mergisi/awesome-hermes-agentWrote 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/mergisi/awesome-hermes-agent/cold-email-personalize)<a href="https://agentmods.dev/skills/mergisi/awesome-hermes-agent/cold-email-personalize"><img src="https://agentmods.dev/badge/skills/mergisi/awesome-hermes-agent/cold-email-personalize/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/mergisi/awesome-hermes-agent/cold-email-personalize"><img src="https://agentmods.dev/badge/skills/mergisi/awesome-hermes-agent/cold-email-personalize.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 | $0.00043 | $0.01699 |
| Opus 5 | $0.00022 | $0.00849 |
| Sonnet 5 | $0.00009 | $0.00340 |
| Haiku 4.5 | $0.00004 | $0.00170 |
Grade A, and why
cold-email-personalize 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 11d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cold Email Personalize
Write the opening line of a cold email that doesn't sound like a cold email. The skill takes a prospect (LinkedIn URL, company domain, or just name + role) and writes a 4-line first message that hooks on a specific signal — a recent hire, a product launch, a podcast quote, a funding round, a public tweet — then asks one clear question.
What this skill does
For each prospect:
- Enrich the prospect — pull from the input (LinkedIn URL, company domain, name+role) and supplement with public signals: recent hires (LinkedIn jobs page), product launches (Product Hunt / changelogs / blog), podcast appearances, funding announcements (Crunchbase / Twitter), recent tweets, GitHub activity if technical role.
- Pick the strongest signal — rank the signals by recency and relevance. The strongest is usually a public commitment (just hired, just launched, just funded) within the last 14 days.
- Write a 4-line message:
- Line 1: signal-driven hook (what they did, when, why it caught your eye)
- Line 2: one-sentence relevance bridge (why your product matters given that signal)
- Line 3: concrete result you've seen for similar companies (with a number, not a vibe)
- Line 4: one specific question, not "Are you free for a 15-min call?"
- Refuse generic openers — the SKILL.md is configured to reject "I noticed your company...", "I came across [name]...", "I see you're working on...", "Hope you're doing well." If the available signal is too weak, the skill says so explicitly instead of writing weak copy.
- Output — markdown with the email body + a one-line "why this signal" note for your records.
What this skill does NOT do
- It does NOT send the email. Delivery is your call. Pair with a sending tool (Lemlist, Smartlead, Instantly, your own SMTP) and human approval before send.
- It does NOT scrape Sales Navigator at scale (that's a TOS issue). Bring data from Apollo, Clay, or your existing list.
- It does NOT write the follow-up sequence. That's a separate skill (coming soon).
- It does NOT guarantee replies. Reply rate depends on signal quality + offer fit. The skill optimizes the floor, not the ceiling.
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.
- 11d ago First seen · 135 lines · 43 tokens per session scan A 254d600189da
cold-email-personalize is a skill published in the GitHub repository mergisi/awesome-hermes-agent (2 stars, last pushed 4mo ago), licensed MIT. It adds 43 tokens to every session and 1,699 once invoked, about $0.0002 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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