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/global-mindee/way/prompt-engineeringnpx skills add Global-mindee/WAY --skill prompt-engineeringgit clone --depth 1 https://github.com/Global-mindee/WAYWrote 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/global-mindee/way/prompt-engineering)<a href="https://agentmods.dev/skills/global-mindee/way/prompt-engineering"><img src="https://agentmods.dev/badge/skills/global-mindee/way/prompt-engineering.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 | $0.00024 | $0.01036 |
| Opus 5 | $0.00012 | $0.00518 |
| Sonnet 5 | $0.00005 | $0.00207 |
| Haiku 4.5 | $0.00002 | $0.00104 |
Grade A, and why
prompt-engineering 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Engineering
Structured System Prompt
You are a senior code reviewer. Your role is to analyze pull requests for:
1. Correctness - logic errors, edge cases, off-by-one errors
2. Security - injection, authentication, data exposure
3. Performance - N+1 queries, unnecessary allocations, missing indexes
4. Maintainability - naming, complexity, test coverage
For each issue found, respond with:
- Severity: critical | warning | suggestion
- File and line reference
- What is wrong
- How to fix it (with code snippet)
If the code is well-written, say so briefly. Do not invent problems.
Structure system prompts with role, scope, output format, and constraints. Be explicit about what the model should NOT do.
Chain-of-Thought
Analyze this database query for performance issues.
Think step by step:
1. Identify the tables and joins involved
2. Check if appropriate indexes exist for the WHERE and JOIN conditions
3. Look for full table scans or cartesian products
4. Estimate the row count at each step
5. Suggest specific index creation or query restructuring
Query:
SELECT o.*, u.name, p.title
FROM orders o
JOIN users u ON o.user_id = u.id
JOIN products p ON o.product_id = p.id
WHERE o.created_at > '2024-01-01'
AND u.country = 'US'
ORDER BY o.created_at DESC
LIMIT 50;
Chain-of-thought prompting improves accuracy on reasoning tasks by forcing the model to show intermediate steps.
Few-Shot Examples
Convert natural language to SQL. Follow these examples:
Input: "How many orders were placed last month?"
Output: SELECT COUNT(*) FROM orders WHERE created_at >= DATE_TRUNC('month', CURRENT_DATE - INTERVAL '1 month') AND created_at < DATE_TRUNC('month', CURRENT_DATE);
Input: "Top 5 customers by total spending"
Output: SELECT customer_id, SUM(total_amount) AS total_spent FROM orders GROUP BY customer_id ORDER BY total_spent DESC LIMIT 5;
Input: "Products that have never been ordered"
Output: SELECT p.* FROM products p LEFT JOIN order_items oi ON p.id = oi.product_id WHERE oi.id IS NULL;
Now convert:
Input: "Average order value per country for the last quarter"
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 · 142 lines · 24 tokens per session scan A 84244ee30587
prompt-engineering is a skill published in the GitHub repository Global-mindee/WAY (11 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 1,036 once invoked, about $0.0001 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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