Prompt Engineer Lite Pack

    1

    Turn a fuzzy task into a reusable LLM prompt with context boundaries, constraints, output schema, and test cases.

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    Works with the AI tools you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseOpenClawOpenClaw+21 more

    Prompt Engineer Lite Pack

    Example session with this skill installed

    Turn this rough request into a production-ready prompt: “Review customer interview notes and identify the top product problems.” Audience: a product manager. Output: a prioritized table with evidence and confidence. Do not invent facts.

    • Read your context and instructions
    • Compiled the prompt engineer lite
    • Generated the UI component

    Goal & assumptions

    Create a repeatable synthesis prompt for a product manager. The notes are the only evidence source; no external facts are assumed.

    Prompt draft

    You are a careful product research analyst.
    
    Task: Review the customer interview notes below and identify the most important product problems.
    
    Inputs
    - Interview notes: {{paste_notes}}
    - Product context (optional): {{context_or_Unknown}}
    
    Method
    1. Extract each distinct problem and preserve the speaker’s meaning.
    2. Group duplicates and near-duplicates.
    3. Rank using frequency, severity, and evidence strength. Do not infer a problem without a quote or explicit note.
    4. Separate observed evidence from interpretation.
    
    Output
    1. Table: Rank | Problem | Evidence quotes | Frequency (if countable) | Severity | Confidence | Open question.
    2. A short “What we do not know” section.
    3. Three next-step interview or product questions.
    
    Constraints
    - Use only the supplied notes.
    - Quote or point to the relevant note for every ranked problem.
    - If unsupported, write Unknown.
    

    Quality checks

    • Every ranked item has traceable evidence.
    • Unknowns are labeled, not filled with guesses.
    • Problems are distinct and actionable.
    • Output matches the requested table and next-step sections.

    How to iterate

    Add a severity rubric or target segment definition for more consistent ranking.

    prompt-engineer-lite-pack.tsx

    TSX · React component

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Prompt Engineer Lite is a concise, honest starter workflow for prompt engineering.

    It helps your agent clarify goals, audience, inputs, constraints, and success criteria; choose a practical prompt pattern; draft explicit prompts with output formats and quality checks; flag missing information instead of guessing; and provide safe fallbacks for conflicting or unsafe requests.

    Use it for one-off prompt refinement, structured extraction, drafting, critique-and-revise, and small production experiments. It does not claim to run tests or provide hidden model access.

    For deeper prompt systems, evaluation matrices, multi-agent orchestration, and reusable prompt libraries, see Cygnix Labs paid packs.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

      Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.

    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

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    Click the path to copy it. Create the folder if it does not exist yet.

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