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 SZoloth/skill-pack --skill prompt-engineergit clone --depth 1 https://github.com/SZoloth/skill-packWrote 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/szoloth/skill-pack/prompt-engineer)<a href="https://agentmods.dev/skills/szoloth/skill-pack/prompt-engineer"><img src="https://agentmods.dev/badge/skills/szoloth/skill-pack/prompt-engineer/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/szoloth/skill-pack/prompt-engineer"><img src="https://agentmods.dev/badge/skills/szoloth/skill-pack/prompt-engineer.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 | $0.00066 | $0.01090 |
| Opus 5.5 | $0.00026 | $0.00436 |
| Sonnet 5.5 | $0.00013 | $0.00218 |
| Haiku 4.5 | $0.00007 | $0.00109 |
Grade A, and why
prompt-engineer 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Engineer
This skill helps create high-quality prompts and instructions for AI systems by treating AI as a genius human teammate who needs clear, context-rich communication.
Core Philosophy
This skill is built on two foundational principles:
- The Genius Intern Framework: Treat AI like a brilliant generalist who can figure things out but needs context about what "good" looks like in your specific situation
- Async Remote Teammate: Write for AI the way you'd write for a smart remote colleague—clear, comprehensive, and decisively opinionated
Modern AI models have both high intelligence and high emotional intelligence. They don't need tricks or "prompt engineering hacks"—they need what any smart remote teammate needs: clear written communication with sufficient context.
Reference Materials
This skill includes three core reference documents. Read them in full as needed:
Always Load First
Writing for AI Teammates - Core philosophy covering:
- Why "prompt engineering" is about clear writing, not tricks
- The 37signals parallel (async remote culture)
- Brevity-clarity balance
- Progressive disclosure ("inverted pyramid")
Load this file at the start of every prompt creation task. It's your primary reference.
Then Load Prompt Framework
Prompt Framework - Comprehensive guide covering:
- Three prompt types (Do This / Know How / Learn Domain)
- Universal principles (examples with reasoning, decision frameworks, visual structure)
- Type-specific patterns and structures
- Anti-patterns to avoid
Always load read this detailed framework to understand best practices based on how Anthropic writes their prompts.
Load Only for GPT-5 Targets
GPT-5 Prompting Guide - GPT-5-specific patterns:
- Avoiding contradictory instructions (critical for GPT-5)
- Calibrating autonomy vs asking questions
- Tool preambles and progress updates
- Self-reflection for quality
- Planning protocols
What ships with it
3 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 · 124 lines · 66 tokens per session scan A 9769dc6eb4ee
prompt-engineer is a skill published in the GitHub repository SZoloth/skill-pack (14 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 1,090 once invoked, about $0.0003 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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