/workshop-facilitation

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.

Input

**Nothing required** — this skill defines the facilitation protocol other interactive skills follow. **Also useful:** If invoked standalone, name the session you want facilitated and any context for it; that context carries into the session as answers already given.

Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended `ARGUMENTS:` line — counts as answers already given. Use it and skip whatever it covers; don't re-ask.

**Arriving empty-handed? That works too.** When another skill references this protocol, that skill's Input section governs what to provide.

**Example invocation:** `Facilitate a 45-minute retro on our failed beta launch using this protocol.`

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."

**Inline input at invocation:** when the user supplies context with the invocation itself, credit it as answers, open at the first unanswered question, and keep progress labels honest (start at `Context Q2/6` if Q1 was covered). Full transcript, including the re-asking anti-pattern: [examples/inline-input-flow.md](examples/inline-input-flow.md).

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.