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 zli12321/LHTB --skill generate-greetinggit clone --depth 1 https://github.com/zli12321/LHTBWrote 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/zli12321/lhtb/generate-greeting)<a href="https://agentmods.dev/skills/zli12321/lhtb/generate-greeting"><img src="https://agentmods.dev/badge/skills/zli12321/lhtb/generate-greeting/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/zli12321/lhtb/generate-greeting"><img src="https://agentmods.dev/badge/skills/zli12321/lhtb/generate-greeting.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 | $0.00015 | $0.00063 |
| Opus 5.5 | $0.00006 | $0.00025 |
| Sonnet 5.5 | $0.00003 | $0.00013 |
| Haiku 4.5 | $0.00002 | $0.00006 |
Grade A, and why
generate-greeting 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 2mo 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
100% identical to generate-greeting — 0 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.
What it actually says
generate-greeting
Generate a greeting message and write it to a file.
Instructions
Write the exact text below to /app/greeting.txt:
Hello from Harbor Skills!
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.
- 2mo ago First seen · 17 lines · 15 tokens per session scan A f08577d626ea
generate-greeting is a skill published in the GitHub repository zli12321/LHTB (568 stars, last pushed 18d ago), licensed Apache-2.0. It adds 15 tokens to every session and 63 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to generate-greeting, differing in 0 lines, and is treated as a copy.
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publish
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generate-greeting
Generate a greeting message and write it to a file.