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 yuri-semenenko/ai-engineering-workspace --skill prompt-engineergit clone --depth 1 https://github.com/yuri-semenenko/ai-engineering-workspaceWrote 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/yuri-semenenko/ai-engineering-workspace/prompt-engineer)<a href="https://agentmods.dev/skills/yuri-semenenko/ai-engineering-workspace/prompt-engineer"><img src="https://agentmods.dev/badge/skills/yuri-semenenko/ai-engineering-workspace/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/yuri-semenenko/ai-engineering-workspace/prompt-engineer"><img src="https://agentmods.dev/badge/skills/yuri-semenenko/ai-engineering-workspace/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 | $0.00045 | $0.00334 |
| Opus 5 | $0.00023 | $0.00167 |
| Sonnet 5 | $0.00009 | $0.00067 |
| Haiku 4.5 | $0.00005 | $0.00033 |
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 9d 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.
What it actually says
Prompt Engineer
Turn rough intent into a structured, decision-oriented prompt for an AI agent.
Principles
- Structure prompts as goal, context, task, constraints, output format, and success criteria.
- Make assumptions and boundaries explicit.
- Use concrete examples only when they clarify behavior.
- Keep prompts token-efficient.
- Avoid generic role filler such as "You are a helpful assistant."
- Make the prompt strict enough to prevent drift and open enough to allow judgment.
Output Structure
Generate prompts with these sections:
- Role — what kind of agent should answer.
- Context — what the agent must know.
- Task — the concrete job.
- Constraints — required behavior and forbidden behavior.
- Output Format — exact response shape.
- Success Criteria — how the result will be judged.
- Edge Cases / Anti-patterns — common failure modes to avoid.
Mirror the user's language in the surrounding response. Generate the prompt itself in English unless the user asks otherwise.
Quality Bar
- Drive clarity, decisions, risks, dependencies, and ownership.
- Include assumptions and explicit non-goals.
- Ask 1-2 clarifying questions if missing context would make the prompt brittle.
- Defer to
rfc,adr, orpr-classifywhen the user wants that artifact directly.
What ships with it
1 file 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.
- 9d ago First seen · 39 lines · 45 tokens per session scan A c8a016073745
prompt-engineer is a skill published in the GitHub repository yuri-semenenko/ai-engineering-workspace (1 stars, last pushed 8d ago), licensed MIT. It adds 45 tokens to every session and 334 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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