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clarify

by team-attention

clarifyは、other分野における実用的なスキルです。複雑な課題への対応力を強化し、業務効率と成果の質を改善します。

396🍴 46📅 2026年1月23日
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SKILL.md


name: clarify description: This skill should be used when the user asks to "clarify requirements", "refine requirements", "specify requirements", "what do I mean", "make this clearer", or when the user's request is ambiguous and needs iterative questioning to become actionable. Also trigger when user says "clarify", "/clarify", or mentions unclear/vague requirements.

Clarify

Transform vague or ambiguous requirements into precise, actionable specifications through iterative questioning.

Purpose

When requirements are unclear, incomplete, or open to multiple interpretations, use structured questioning to extract the user's true intent before any implementation begins.

Protocol

Phase 1: Capture Original Requirement

Record the original requirement exactly as stated:

## Original Requirement
"{user's original request verbatim}"

Identify ambiguities:

  • What is unclear or underspecified?
  • What assumptions would need to be made?
  • What decisions are left to interpretation?

Phase 2: Iterative Clarification

Use AskUserQuestion tool to resolve each ambiguity. Continue until ALL aspects are clear.

Question Design Principles:

  • Specific over general: Ask about concrete details, not abstract preferences
  • Options over open-ended: Provide 2-4 choices (recognition > recall)
  • One concern at a time: Avoid bundling multiple questions
  • Neutral framing: Present options without bias

Loop Structure:

while ambiguities_remain:
    identify_most_critical_ambiguity()
    ask_clarifying_question()  # Use AskUserQuestion tool
    update_requirement_understanding()
    check_for_new_ambiguities()

AskUserQuestion Format:

question: "What authentication method should be used?"
options:
  - label: "Username/Password"
    description: "Traditional email/password login"
  - label: "OAuth"
    description: "Google, GitHub, etc. social login"
  - label: "Magic Link"
    description: "Passwordless email link"

Phase 3: Before/After Comparison

After clarification is complete, present the transformation:

## Requirement Clarification Summary

### Before (Original)
"{original request verbatim}"

### After (Clarified)
**Goal**: [precise description of what user wants]
**Scope**: [what's included and excluded]
**Constraints**: [limitations, requirements, preferences]
**Success Criteria**: [how to know when done]

**Decisions Made**:
| Question | Decision |
|----------|----------|
| [ambiguity 1] | [chosen option] |
| [ambiguity 2] | [chosen option] |

Phase 4: Save Option

Ask if the user wants to save the clarified requirement:

AskUserQuestion:
question: "Save this requirement specification to a file?"
options:
  - label: "Yes, save to file"
    description: "Save to requirements/ directory"
  - label: "No, proceed"
    description: "Continue without saving"

If saving:

  • Default location: requirements/ or project-appropriate directory
  • Filename: descriptive, based on requirement topic (e.g., auth-feature-requirements.md)
  • Format: Markdown with Before/After structure

Ambiguity Categories

Common types to probe:

CategoryExample Questions
ScopeWhat's included? What's explicitly out?
BehaviorEdge cases? Error scenarios?
InterfaceWho/what interacts? How?
DataInputs? Outputs? Format?
ConstraintsPerformance? Compatibility?
PriorityMust-have vs nice-to-have?

Examples

Example 1: Vague Feature Request

Original: "Add a login feature"

Clarifying questions (via AskUserQuestion):

  1. Authentication method? → Username/Password
  2. Registration included? → Yes, self-signup
  3. Session duration? → 24 hours
  4. Password requirements? → Min 8 chars, mixed case

Clarified:

  • Goal: Add username/password login with self-registration
  • Scope: Login, logout, registration, password reset
  • Constraints: 24h session, bcrypt, rate limit 5 attempts
  • Success: User can register, login, logout, reset password

Example 2: Bug Report

Original: "The export is broken"

Clarifying questions:

  1. Which export? → CSV
  2. What happens? → Empty file
  3. When did it start? → After v2.1 update
  4. Steps to reproduce? → Export any report

Clarified:

  • Goal: Fix CSV export producing empty files
  • Scope: CSV only, other formats work
  • Constraint: Regression from v2.1
  • Success: CSV contains correct data matching UI

Rules

  1. No assumptions: Ask, don't assume
  2. Preserve intent: Refine, don't redirect
  3. Minimal questions: Only what's needed
  4. Respect answers: Accept user decisions
  5. Track changes: Always show before/after

スコア

総合スコア

70/100

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