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workshop-facilitation

by @deanpetersv1.0.0
3.7(0)

提供分步式工作坊引导,包含编号建议,确保会议高效进行,达成预期目标。

Workshop DesignFacilitation SkillsMeeting ManagementGroup DynamicsTraining & DevelopmentGitHub
安装方式
npx skills add deanpeters/Product-Manager-Skills --skill workshop-facilitation
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Before / After 效果对比

1
使用前

组织工作坊时,流程混乱,参与者注意力不集中,讨论效率低下,难以达成预期成果。

使用后

采用结构化、多轮次的工作坊引导模式,确保了会议节奏一致、选项清晰、进度可追踪,显著提升了工作坊效果和参与者满意度。

description SKILL.md


name: workshop-facilitation description: Facilitate workshop sessions in a one-step, multi-turn flow. Use when an interactive skill needs consistent pacing, options, and progress tracking. intent: >- Provide the canonical facilitation pattern for interactive skills: one step at a time, with clear progress, adaptive recommendations at decision points, and predictable interruption handling. type: interactive theme: workshops-facilitation best_for:

  • "Adding structured facilitation to any PM workshop or guided session"
  • "Running interactive sessions with numbered recommendations and progress tracking"
  • "Ensuring your workshops stay on track and end with actionable choices" scenarios:
  • "I want to run a structured positioning workshop with my product team — set up the facilitation protocol"
  • "Help me facilitate a discovery sprint kickoff with clear questions, options, and progress labels" estimated_time: "varies by workshop"

Purpose

Provide the canonical facilitation pattern for interactive skills: one step at a time, with clear progress, adaptive recommendations at decision points, and predictable interruption handling.

Key Concepts

  • One-step-at-a-time: Ask a single targeted question per turn.
  • Session heads-up + entry mode: Start by setting expectations and offering Guided, Context dump, or Best guess mode.
  • Progress visibility: Show user-facing progress labels like Context Qx/8 and Scoring Qx/5.
  • Decision-point recommendations: Use enumerated options only when a choice is needed, not after every answer.
  • Quick-select response options: For regular context/scoring questions, provide concise numbered answer options plus Other (specify) when useful.
  • Flexible selection parsing: Accept #1, 1, 1 and 3, 1,3, or custom text, then synthesize multi-select choices.
  • Context-aware progression: Build on previous answers and avoid re-asking resolved questions.
  • Interruption-safe flow: Answer meta questions directly (for example, "how many left?"), restate status, then resume.
  • Fast path: If the user requests a single-shot output, skip multi-turn facilitation and deliver a condensed result.

Application

  1. Start with a brief heads-up on estimated time and number of questions.
  2. Ask the user to choose an entry mode:
    • 1 Guided mode (one question at a time)
    • 2 Context dump (paste known context; skip redundancies)
    • 3 Best guess mode (infer missing details and label assumptions)
  3. Run one question per turn and wait for an answer before continuing.
  4. Keep questions plain-language; include a short example response format when helpful.
  5. Show progress each turn:
    • Context Qx/8 during context collection
    • Scoring Qx/5 during assessment/scoring
  6. Ask follow-up clarifications only when they materially improve recommendation quality.
  7. For regular context/scoring questions, offer quick-select numbered response options when practical:
    • Keep options concise and mutually exclusive when possible.
    • Include Other (specify) if likely answers are open-ended.
    • Accept multi-select responses like 1,3 or 1 and 3.
  8. Provide numbered recommendations only at decision points:
    • after context synthesis,
    • after maturity/profile synthesis,
    • during priority/action-plan selection.
  9. Accept numeric or custom choices, synthesize multi-select choices, and continue.
  10. If interrupted by a meta question, answer directly, then restate progress and pending question.
  11. If the user says stop/pause, halt immediately and wait for explicit resume.
  12. End with a clear summary, decisions made, and (if best guess mode was used) an Assumptions to Validate list.

Examples

Opening: "Quick heads-up: this should take about 7-10 minutes and around 10 questions. How do you want to start?

  1. Guided mode
  2. Context dump
  3. Best guess mode"

User: "2"

Facilitator: "Paste what you already know. I’ll skip answered areas and ask only what’s missing."

Decision point after synthesis:

  1. Prioritize Context Design (Recommended)
  2. Prioritize Agent Orchestration
  3. Prioritize Team-AI Facilitation

User: "1 and 3"

Facilitator: "Great. We’ll run Context Design first, with Team-AI Facilitation in parallel."

Common Pitfalls

  • Asking multiple questions in the same turn.
  • Offering recommendations after every answer (creates interaction drag).
  • Using shorthand labels without plain-language questions.
  • Hiding progress, so users don't know how much remains.
  • Ignoring the user's chosen option or custom direction.
  • Failing to label assumptions when running in best-guess mode.

References

  • Use as the source of truth for interactive facilitation behavior.
  • Apply alongside workshop skills in skills/*-workshop/SKILL.md and advisor-style interactive skills.

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统计数据

安装量292
评分3.7 / 5.0
版本1.0.0
更新日期2026年3月16日
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创建2026年3月16日
最后更新2026年3月16日