/workshop-facilitation
Facilitate workshop sessions in a one-step, multi-turn flow. Use when an interactive skill needs consistent pacing, options, and progress tracking.
$ npx -y skills add getcrew44/crew44 --skill workshop-facilitation --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/workshop-facilitation
Context preview
The summary Claude sees to decide when to auto-load this skill.
Facilitate workshop sessions in a one-step, multi-turn flow. Use when an interactive skill needs consistent pacing, options, and progress tracking.
SKILL.md
workshop-facilitation.SKILL.mdname: 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.
Read more
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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Repo: getcrew44/crew44
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Open skill - /receiving-code-review
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Open skill - /requesting-code-review
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