workshop-facilitation

workshop-facilitation is a skill for Claude Code, Codex from getcrew44/crew44. It costs 36 tokens per session (1,057 once invoked), scanned A, original, MIT.

A facilitation pattern for running interactive workshops one step at a time. It provides pacing, progress tracking, response options, adaptive questions, and ways to handle interruptions or single-shot requests.

In plain words
What is it for?
Use it to design guided workshops that collect context, ask focused questions, offer decisions when needed, and produce a structured result.
Why use it?
Multi-turn workshops can become confusing when questions are repeated, progress is unclear, or decisions are poorly timed. This pattern keeps the session focused and responsive.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to design guided workshops that collect context, ask focused questions…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/getcrew44/crew44/workshop-facilitation
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add getcrew44/crew44 --skill workshop-facilitation
Clone the repo
git clone --depth 1 https://github.com/getcrew44/crew44

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for workshop-facilitation

README.md
[![agentmods](https://agentmods.dev/badge/skills/getcrew44/crew44/workshop-facilitation.svg)](https://agentmods.dev/skills/getcrew44/crew44/workshop-facilitation)
Your own site
<a href="https://agentmods.dev/skills/getcrew44/crew44/workshop-facilitation"><img src="https://agentmods.dev/badge/skills/getcrew44/crew44/workshop-facilitation.svg" alt="Measured on agentmods" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,057 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00036 $0.01057
Opus 5 $0.00018 $0.00528
Sonnet 5 $0.00007 $0.00211
Haiku 4.5 $0.00004 $0.00106

Measured 3d ago against content hash c39d8e2d5fa3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

workshop-facilitation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

daemon/internal/presets/defaultcrew/skills/product/workshop-facilitation/SKILL.md · 88 lines

How it starts

The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.

Read the full file on GitHub · 88 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 88 lines · 36 tokens per session scan A c39d8e2d5fa3

Subscribe to this mod's changes

workshop-facilitation is a skill published in the GitHub repository getcrew44/crew44 (359 stars, last pushed 2mo ago), licensed MIT. It adds 36 tokens to every session and 1,057 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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