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 agentmods add skills/aidotnet/moyucode/prompt-engineernpx skills add AIDotNet/MoYuCode --skill prompt-engineergit clone --depth 1 https://github.com/AIDotNet/MoYuCodeWrote 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/aidotnet/moyucode/prompt-engineer)<a href="https://agentmods.dev/skills/aidotnet/moyucode/prompt-engineer"><img src="https://agentmods.dev/badge/skills/aidotnet/moyucode/prompt-engineer.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.00710 |
| Opus 5 | $0.00017 | $0.00355 |
| Sonnet 5 | $0.00007 | $0.00142 |
| Haiku 4.5 | $0.00003 | $0.00071 |
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 5d 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Engineer Skill
Description
Design and optimize prompts for AI models using proven techniques.
Trigger
/promptcommand- User requests prompt design
- User needs AI prompt optimization
Prompt
You are a prompt engineering expert that creates effective AI prompts.
System Prompt Template
You are a [ROLE] that [PRIMARY_FUNCTION].
## Core Responsibilities
1. [Responsibility 1]
2. [Responsibility 2]
3. [Responsibility 3]
## Guidelines
- Always [guideline 1]
- Never [guideline 2]
- When uncertain, [fallback behavior]
## Output Format
[Specify exact format expected]
## Examples
[Provide 2-3 examples of ideal responses]
Few-Shot Learning
Classify the sentiment of customer reviews.
Examples:
Review: "This product exceeded my expectations! Fast shipping too."
Sentiment: positive
Review: "Broke after one week. Complete waste of money."
Sentiment: negative
Review: "It works as described. Nothing special."
Sentiment: neutral
Now classify:
Review: "{user_input}"
Sentiment:
Chain-of-Thought
Solve this step by step:
Problem: A store has 150 apples. They sell 40% on Monday and 30 more on Tuesday. How many remain?
Let me think through this:
1. Starting amount: 150 apples
2. Monday sales: 150 × 0.40 = 60 apples sold
3. After Monday: 150 - 60 = 90 apples
4. Tuesday sales: 30 apples sold
5. After Tuesday: 90 - 30 = 60 apples
Answer: 60 apples remain
Structured Output
Extract information from the text and return as JSON.
Text: "John Smith, age 32, works as a software engineer at Google in Mountain View. He can be reached at [email protected]."
Output format:
{
"name": "string",
"age": number,
"occupation": "string",
"company": "string",
"location": "string",
"email": "string"
}
Response:
{
"name": "John Smith",
"age": 32,
"occupation": "software engineer",
"company": "Google",
"location": "Mountain View",
"email": "[email protected]"
}
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.
- 5d ago First seen · 132 lines · 35 tokens per session scan A 91d4fd55db31
prompt-engineer is a skill published in the GitHub repository AIDotNet/MoYuCode (84 stars, last pushed 7mo ago), licensed MIT. It adds 35 tokens to every session and 710 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 2026-08-30.
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