Claude Skill

interview-me

Imported from paulrberg/agent-skills/skills/interview-me.

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Download paulrberg-agent-skills-skills_interview-me-913232a.zip · 1 KB
Part of paulrberg/agent-skills — 42 skills

Install

skills CLI npx skills add https://github.com/PaulRBerg/agent-skills/tree/main/skills/interview-me
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install paulrberg-agent-skills@llmmart
Git git clone https://github.com/PaulRBerg/agent-skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole paulrberg/agent-skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Interview Me

This skill is coordination-exempt: skip the ai-coord gate for its declared work.

Clarify what the user wants through a focused, conversational interview without exhausting every possible branch.

Workflow

  1. Extract the current objective, audience, constraints, assumptions, and already-made choices. Investigate facts available from the conversation, codebase, or supplied evidence instead of asking for them.
  2. Ask exactly one concise question per turn in plain conversational language. Format every question turn as ### 💬 Question <N> — <topic>, followed by **🧭 Context**, optional **🎯 Recommended**, and **❓ Question** sections, with each label on its own line. Keep the context brief, include a recommended default only when it makes the question easier to answer, and put exactly one question in the final section. Choose the highest-leverage question whose answer could materially change the direction or next step.
  3. Treat three to five questions as a soft target, not a quota or hard cap. Stop earlier when the direction is already clear. Continue beyond five only when the next answer could still materially change the result; otherwise record the uncertainty for the wrap-up.
  4. Favor intent, scope, success criteria, audience, and key tradeoffs. Follow the threads the user emphasizes instead of mechanically covering every interface, failure mode, operational concern, or other domain.
  5. Briefly acknowledge or synthesize an answer as ✅ Noted: <choice or implication> only when it advances the conversation. Do not use decision cards, progress counts, exhaustive checklists, repeated recaps, or a formal decision record. Do not reopen settled choices unless new evidence conflicts with them.
  6. Finish immediately when the user asks to stop or when further questions would add little value. Return ### 🧭 Summary, ### ✅ Key choices, optional ### ❓ Open questions, and ### 🏁 Next step. Keep the wrap-up concise and do not end with another question.

Completion requires a clear summary of the user's direction, the choices that materially shape it, any unresolved uncertainty worth preserving, and one practical next step.

Files (agent-skills)
  • agents
    • openai.yaml 42 B
      policy:
        allow_implicit_invocation: true
      
  • SKILL.md 2.5 KB
    ---
    coordination: exempt
    name: interview-me
    description:
      Interview the user about a plan, idea, or design through a short sequence of high-leverage questions, then summarize
      the direction and next step. Use when the user wants a relaxed interview, lightweight clarification, or says
      "interview me", without exhaustive grilling.
    ---
    
    # Interview Me
    
    This skill is coordination-exempt: skip the ai-coord gate for its declared work.
    
    Clarify what the user wants through a focused, conversational interview without exhausting every possible branch.
    
    ## Workflow
    
    1. Extract the current objective, audience, constraints, assumptions, and already-made choices. Investigate facts
       available from the conversation, codebase, or supplied evidence instead of asking for them.
    2. Ask exactly one concise question per turn in plain conversational language. Format every question turn as
       `### 💬 Question <N> — <topic>`, followed by `**🧭 Context**`, optional `**🎯 Recommended**`, and `**❓ Question**`
       sections, with each label on its own line. Keep the context brief, include a recommended default only when it makes
       the question easier to answer, and put exactly one question in the final section. Choose the highest-leverage
       question whose answer could materially change the direction or next step.
    3. Treat three to five questions as a soft target, not a quota or hard cap. Stop earlier when the direction is already
       clear. Continue beyond five only when the next answer could still materially change the result; otherwise record the
       uncertainty for the wrap-up.
    4. Favor intent, scope, success criteria, audience, and key tradeoffs. Follow the threads the user emphasizes instead of
       mechanically covering every interface, failure mode, operational concern, or other domain.
    5. Briefly acknowledge or synthesize an answer as `✅ Noted: <choice or implication>` only when it advances the
       conversation. Do not use decision cards, progress counts, exhaustive checklists, repeated recaps, or a formal
       decision record. Do not reopen settled choices unless new evidence conflicts with them.
    6. Finish immediately when the user asks to stop or when further questions would add little value. Return
       `### 🧭 Summary`, `### ✅ Key choices`, optional `### ❓ Open questions`, and `### 🏁 Next step`. Keep the wrap-up
       concise and do not end with another question.
    
    Completion requires a clear summary of the user's direction, the choices that materially shape it, any unresolved
    uncertainty worth preserving, and one practical next step.
    

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