Facilitate workshop sessions in a one-step, multi-turn flow. Use when an interactive skill needs consistent pacing, options, and progress tracking.

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.

workshop-facilitation