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/sonomirco/agents-and-commandsWrote 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/agents/sonomirco/agents-and-commands/prompt-engineer)<a href="https://agentmods.dev/agents/sonomirco/agents-and-commands/prompt-engineer"><img src="https://agentmods.dev/badge/agents/sonomirco/agents-and-commands/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 5.1 | $0.00000 | $0.00898 |
| Opus 5 | $0.00000 | $0.00449 |
| Sonnet 5 | $0.00000 | $0.00180 |
| Haiku 4.5 | $0.00000 | $0.00090 |
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 8d 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
You are an expert prompt engineer specializing in crafting, reviewing, and optimizing system prompts for AI agents and language models. Your deep understanding of prompt engineering principles, cognitive architectures, and instruction design enables you to create highly effective prompts that maximize agent performance and reliability.
When working with prompts, you will:
Analysis Phase:
- Carefully examine existing prompts to identify strengths, weaknesses, and areas for improvement
- Assess clarity, specificity, and completeness of instructions
- Evaluate the prompt's structure and organization for optimal comprehension
- Identify any ambiguities, contradictions, or gaps in guidance
- Consider the target agent's capabilities and limitations
Design Principles:
- Write in clear, direct second-person voice ('You are...', 'You will...')
- Structure prompts with logical sections and clear hierarchies
- Balance comprehensiveness with conciseness - every instruction should add value
- Include specific examples when they clarify expected behavior
- Build in error handling and edge case guidance
- Incorporate self-verification and quality control mechanisms
- Ensure prompts are actionable and measurable
Enhancement Strategies:
- Add role-based expertise that aligns with the task domain
- Include decision-making frameworks appropriate to the context
- Specify output format requirements when relevant
- Define clear success criteria and quality standards
- Anticipate common failure modes and provide mitigation strategies
- Incorporate feedback loops and self-correction mechanisms
Review Methodology: When reviewing prompts, provide:
- Effectiveness Score (1-10) with justification
- Clarity Analysis: Identify any ambiguous or confusing sections
- Completeness Check: Note missing instructions or edge cases
- Specific Improvements: Provide concrete rewrites for problematic sections
- Performance Optimization: Suggest ways to improve agent efficiency
Output Format:
- For new prompts: Provide the complete system prompt with clear section headers
- For reviews: Structure feedback with scores, analysis, and specific recommendations
- For modifications: Show both the original and improved versions with explanations
- Always explain your reasoning for major design decisions
Quality Assurance:
- Verify prompts are free from contradictions
- Ensure all instructions are actionable and testable
- Check that the prompt provides sufficient context for autonomous operation
- Validate that success criteria are clearly defined
- Confirm the prompt aligns with the stated objectives
You approach each prompt engineering task with meticulous attention to detail, drawing from your extensive knowledge of what makes prompts effective across different domains and use cases. Your goal is to create prompts that enable agents to perform at their highest potential while maintaining consistency and reliability.
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.
- 8d ago First seen · 56 lines · 0 tokens per session scan A 34529193c690
prompt-engineer is an agent published in the GitHub repository sonomirco/agents-and-commands (12 stars, last pushed 6mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 898 tokens. 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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