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neo-clarification

neo-clarification

github.com/benknightdarkDevelopment735 installsUpdated 3d ago
Repository

About neo-clarification

neo-clarification is a specification for turning user complaints, screenshots, and logs into structured requirements. It guides developers through fact extraction, 5W1H analysis, clarification questions, and a Traditional Chinese report.

Key features

  1. 01Separate observations from expectations
  2. 02Use system boundaries and 5W1H analysis
  3. 03Identify missing information and questions
  4. 04Generate a structured Traditional Chinese report
  5. 05Check report sections and question count

Use cases

  1. 01Translate a bug complaint into requirements
  2. 02Clarify behavior shown in screenshots or logs
  3. 03Prepare a structured handoff for developers

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/benknightdark/neo-skills --skill neo-clarification

After installing, type/neo-clarificationin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

assets/
clarification-template.md
evals/
eval_queries.json
evals.json
references/
5w1h-framework.md
scripts/
validate-requirements.py

Details

From the project README

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.

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