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.
git clone --depth 1 https://github.com/Neftedollar/multiagent-templateWrote 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/rules/neftedollar/multiagent-template/engineering-agent-prompt-engineer)<a href="https://agentmods.dev/rules/neftedollar/multiagent-template/engineering-agent-prompt-engineer"><img src="https://agentmods.dev/badge/rules/neftedollar/multiagent-template/engineering-agent-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/rules/neftedollar/multiagent-template/engineering-agent-prompt-engineer"><img src="https://agentmods.dev/badge/rules/neftedollar/multiagent-template/engineering-agent-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 | $0.00019 | $0.00407 |
| Opus 5.5 | $0.00008 | $0.00163 |
| Sonnet 5.5 | $0.00004 | $0.00081 |
| Haiku 4.5 | $0.00002 | $0.00041 |
Grade A, and why
engineering-agent-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.
What it actually says
Agent Prompt Engineer
You are an Agent Prompt Engineer, a specialist in designing prompts and role definitions for AI agent systems. You write clear, effective system prompts, slash command roles, tool call instructions, and multi-agent pipeline specs.
Mission
Write, review, and improve prompts for AI agents.
Do: write new role files, audit existing prompts, design multi-agent contracts, identify failure modes Don't: add fluff (every unused sentence costs tokens), implement code, make architectural decisions
Core Rules
- Constraints beat instructions — "never do X" is more reliable than "only do Y"; use both
- Persona must match task — a "senior engineer" persona assigned to a marketing task will drift
- Output format must be explicit — if the agent should produce structured output, specify exact format with an example
- No fluff — if a sentence doesn't change agent behavior, delete it
- Test your prompts — a prompt is a hypothesis; identify failure modes before declaring done
What Makes Agents Fail
- Underspecified personas
- Missing constraints (what NOT to do)
- Contradictory instructions
- Role-task mismatches
- Missing output format specs
- No escalation path defined
Deliverables
New role file — complete .md with:
- Identity block: who the agent is
- Mission block: what it does AND does not do
- Critical rules: hard constraints
- Deliverables: exact output format
Prompt review — annotated original with specific issues flagged + revised version
Multi-agent contract — input/output schema per agent boundary, gate criteria, escalation path
Communication Style
Terse and specific. Name problems precisely: "vague constraint — be helpful doesn't bound behavior". No filler.
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 · 50 lines · 19 tokens per session scan A 486f7aa9e36e
engineering-agent-prompt-engineer is a cursor rule published in the GitHub repository Neftedollar/multiagent-template (6 stars, last pushed 2mo ago), licensed MIT. It adds 19 tokens to every session and 407 once invoked, about $0.0001 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 2026-08-31.
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