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    Prompt Engineering Specialist

    Prompt Engineering Specialist

    by Arnstein Larsen

    Production prompts grow by accretion — every failure gets another appended rule until the prompt is two thousand words of contradictions that the model navigates unpredictably

    Updated Jun 2026
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    $9.99

    · or 50 credits

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    Included in download

    • Debug and fix inconsistent LLM outputs in production environments
    • Refactor long prompts to improve instruction following and context retention
    • Instant install

    Sample input

    My system prompt for extracting JSON from invoices is failing 20% of the time on multi-page PDFs. It keeps adding conversational text outside the JSON. Help me fix the output format and reliability.

    Sample output

    I've redesigned your prompt using an XML-wrapped output contract. I've added two 'boundary' few-shot examples specifically for multi-page transitions.

    Diagnosis: Format bleed due to weak instruction placement. Deliverable: New System Prompt + 3 Regression Test Cases.

    About This Skill

    Production prompts grow by accretion — every failure gets another appended rule until the prompt is two thousand words of contradictions that the model navigates unpredictably. This skill engineers your prompts properly: the system prompt structure that gives the model a stable role and constraints without fighting itself, few-shot example selection that actually demonstrates the edge cases that matter, output format specifications that parse reliably, and the evaluation harness that tells you when a prompt change made things better vs. just different. It works on new prompts you're designing and existing prompts that have grown into maintenance nightmares. Give it your current prompt, your failure cases, and your target output; it returns a redesigned prompt and the reasoning behind every structural decision so you can maintain it without re-discovering why it was built that way.

    Use Cases

    • Debug and fix inconsistent LLM outputs in production environments
    • Refactor long prompts to improve instruction following and context retention
    • Generate high-quality few-shot examples for complex edge cases
    • Eliminate conversational 'filler' from automated AI agent responses

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    Compatible with SKILL.md-compatible agents including Claude Code and Cursor.

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