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Get Started Free →Facilitate workshop sessions in a one-step, multi-turn flow. Use when an interactive skill needs consistent pacing, options, and progress tracking.
.claude/skills/getcrew44-workshop-facilitation/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 65% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 116% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 12% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 25% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 50% | 0% |
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.
Guided, Context dump, or Best guess mode.Context Qx/8 and Scoring Qx/5.Other (specify) when useful.#1, 1, 1 and 3, 1,3, or custom text, then synthesize multi-select choices.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)Context Qx/8 during context collectionScoring Qx/5 during assessment/scoringOther (specify) if likely answers are open-ended.1,3 or 1 and 3.Assumptions to Validate list.Opening: "Quick heads-up: this should take about 7-10 minutes and around 10 questions. How do you want to start?
User: "2"
Facilitator: "Paste what you already know. I’ll skip answered areas and ask only what’s missing."
Decision point after synthesis:
User: "1 and 3"
Facilitator: "Great. We’ll run Context Design first, with Team-AI Facilitation in parallel."
skills/*-workshop/SKILL.md and advisor-style interactive skills.| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 6,173 | 34,106 | +453% | 1 | 1 | 0% | 979 | 1,614 | +65% | 0 | 0 | — |
case-02 | fail→fail | 6,075 | 3,330 | -45% | 1 | 1 | 0% | 897 | 1,413 | +58% | 0 | 0 | — |
case-03 | fail→pass | 4,378 | 3,094 | -29% | 1 | 1 | 0% | 679 | 1,466 | +116% | 0 | 0 | — |
case-09 | pass→pass | 11,364 | 6,889 | -39% | 1 | 1 | 0% | 1,646 | 1,906 | +16% | 0 | 0 | — |
case-04 | pass→pass | 9,396 | 5,296 | -44% | 1 | 1 | 0% | 1,342 | 1,745 | +30% | 0 | 0 | — |
case-05 | fail→pass | 11,530 | 6,144 | -47% | 1 | 1 | 0% | 1,674 | 1,875 | +12% | 0 | 0 | — |
case-06 | fail→pass | 12,101 | 7,495 | -38% | 1 | 1 | 0% | 1,708 | 2,139 | +25% | 0 | 0 | — |
case-07 | fail→pass | 8,257 | 5,663 | -31% | 1 | 1 | 0% | 1,181 | 1,776 | +50% | 0 | 0 | — |
case-08 | fail→pass | 2,946 | 4,785 | +62% | 1 | 1 | 0% | 448 | 1,666 | +272% | 0 | 0 | — |
case-10 | fail→fail | 7,906 | 3,196 | -60% | 1 | 1 | 0% | 1,139 | 1,422 | +25% | 0 | 0 | — |
case-11 | fail→pass | 5,559 | 4,898 | -12% | 1 | 1 | 0% | 704 | 1,678 | +138% | 0 | 0 | — |
case-12 | pass→pass | 4,916 | 3,623 | -26% | 1 | 1 | 0% | 687 | 1,413 | +106% | 0 | 0 | — |
case-13 | pass→pass | 15,004 | 10,969 | -27% | 1 | 1 | 0% | 2,229 | 2,566 | +15% | 0 | 0 | — |
case-14 | fail→fail | 10,456 | 3,164 | -70% | 1 | 1 | 0% | 1,446 | 1,376 | -5% | 0 | 0 | — |
case-15 | fail→pass | 5,962 | 4,076 | -32% | 1 | 1 | 0% | 868 | 1,547 | +78% | 0 | 0 | — |
case-16 | fail→pass | 5,355 | 4,746 | -11% | 1 | 1 | 0% | 848 | 1,696 | +100% | 0 | 0 | — |
case-17 | pass→pass | 4,976 | 5,046 | +1% | 1 | 1 | 0% | 719 | 1,704 | +137% | 0 | 0 | — |
case-18 | fail→pass | 13,164 | 4,252 | -68% | 1 | 1 | 0% | 1,909 | 1,564 | -18% | 0 | 0 | — |
case-19 | fail→pass | 4,197 | 6,709 | +60% | 1 | 1 | 0% | 567 | 1,923 | +239% | 0 | 0 | — |
case-20 | fail→pass | 34,911 | 18,763 | -46% | 1 | 1 | 0% | 6,177 | 3,959 | -36% | 0 | 0 | — |
case-21 | pass→pass | 5,986 | 5,471 | -9% | 1 | 1 | 0% | 1,021 | 1,768 | +73% | 0 | 0 | — |
case-22 | pass→fail | 19,449 | 3,879 | -80% | 1 | 1 | 0% | 2,928 | 1,350 | -54% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +50 percentage points is the difference between those two pass rates over the 22 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.