workshop-facilitation
About
This skill provides structured facilitation for interactive workshops by guiding users through a step-by-step, multi-turn flow. It maintains consistent pacing with progress tracking and offers adaptive recommendations at decision points. Use it when you need to run guided sessions like product workshops that require clear options and predictable interruption handling.
Quick Install
Claude Code
Recommendednpx skills add deanpeters/Product-Manager-Skills -a claude-code/plugin add https://github.com/deanpeters/Product-Manager-Skillsgit clone https://github.com/deanpeters/Product-Manager-Skills.git ~/.claude/skills/workshop-facilitationCopy and paste this command in Claude Code to install this skill
Documentation
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, orBest guessmode. - Progress visibility: Show user-facing progress labels like
Context Qx/8andScoring 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
- Start with a brief heads-up on estimated time and number of questions.
- Ask the user to choose an entry mode:
1Guided mode (one question at a time)2Context dump (paste known context; skip redundancies)3Best guess mode (infer missing details and label assumptions)
- Run one question per turn and wait for an answer before continuing.
- Keep questions plain-language; include a short example response format when helpful.
- Show progress each turn:
Context Qx/8during context collectionScoring Qx/5during assessment/scoring
- Ask follow-up clarifications only when they materially improve recommendation quality.
- 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
1,3or1 and 3.
- Provide numbered recommendations only at decision points:
- after context synthesis,
- after maturity/profile synthesis,
- during priority/action-plan selection.
- Accept numeric or custom choices, synthesize multi-select choices, and continue.
- If interrupted by a meta question, answer directly, then restate progress and pending question.
- If the user says stop/pause, halt immediately and wait for explicit resume.
- End with a clear summary, decisions made, and (if best guess mode was used) an
Assumptions to Validatelist.
Examples
Opening: "Quick heads-up: this should take about 7-10 minutes and around 10 questions. How do you want to start?
- Guided mode
- Context dump
- 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:
- Prioritize Context Design (Recommended)
- Prioritize Agent Orchestration
- 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.mdand advisor-style interactive skills.
GitHub Repository
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