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Neo clarification

Skill Benknightdark/neo-skills/skills/neo-clarification

Neo Skills 是專為現代 AI Agent 設計的全方位能力擴充套件。本專案透過標準化的通訊架構，為 AI 代理安裝可插拔的「技能模組 (Skills)」，使其不僅僅是一個聊天機器人，而是能轉化為具備「感知-推理-行動」能力的多領域專家。

Install
npx -y skills add Benknightdark/neo-skills --skill neo-clarification

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 7 stars7 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use this skill when the user gives vague, emotional, fragmented, screenshot-based, or complaint-style requirements and wants them converted into structured specs, acceptance criteria, or clarifying questions.

SKILL.md

3.2 KB, as published. Nobody here has run it

Requirement Clarification Specifications

Apply the Inversion & Generator Pattern. Follow this protocol strictly to translate raw, chaotic user complaints and screenshots into clean, structured system specifications.

1. Perceive Phase

  1. Information Extraction:

    • Carefully read the user's text and inspect any attached screenshots or logs.
    • Filter out emotional noise, frustrations, and blame.
    • Separate objective facts (what is currently happening or visible) from user expectations (what they wanted to accomplish).

  2. Identify System Boundaries:

    • Determine the scope, domain, and potential technical layers affected by the feedback (e.g., frontend rendering, network APIs, database states, permission groups).

2. Reason Phase

  1. Load Analysis Framework:

    • Always read the external analysis guide before starting your deduction: 5w1h-framework.md

  2. Context Reconstruction (5W1H):

    • Map the extracted facts to the 5W1H framework (Who, Where, When, What, Why, How).
    • Formulate logical hypotheses on the root causes of UI anomalies or system behaviors.

  3. Identify Gaps:

    • Pinpoint critical missing information (e.g., browser environment, specific action steps, parameters, error logs).
    • Prepare a list of clarifying questions to ask the user.

3. Act Phase

Generate a structured "Requirement Translation and Clarification Report" strictly in Traditional Chinese (Taiwan). Follow these steps:

  1. Load Output Template:

  2. Compile the Report:

    • Fill in the template using Traditional Chinese.
    • Context Restoration: Present objective facts concisely without emotional adjectives.
    • User Story: Use the strict format: "身為... 我想要... 以便於..."
    • System Requirements & Hypotheses: Highlight key rendering, API, and validation checkpoints for the development team.
    • Open Questions: List between 2 and 10 polite, precise, and constructive clarifying questions.

  3. Self-Validation:

    • Proactively validate your report using the non-interactive python script: 
      uv run skills/neo-clarification/scripts/validate-requirements.py -i <path_to_saved_report>
      (Or verify mentally that all sections exist and the number of questions is between 2 and 10 before final output).

4. Communication Guidelines

  • Maintain Empathetic Neutrality: Acknowledge the user's difficulty, but never agree that the system is "broken" or "a disaster" in the official report. Use neutral, objective descriptions.
  • Strictly No Guesswork: Do NOT invent features that the user did not hint at. Ask clarifying questions instead.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.