showroom/skills/create-lab/SKILL.md
This skill should be used when the user asks to "create a lab module", "write a workshop module", "build a Showroom lab", "convert docs to a lab", "write a hands-on exercise", "create an AsciiDoc module", or "turn this documentation into a lab exercise".
npx skillsauth add rhpds/rhdp-skills-marketplace showroom:create-labInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Orchestrates agents to create Red Hat Showroom workshop or demo content. Two modes: interactive (human) and headless (Publishing House via ph_payload).
This skill is an orchestrator. Generation and review are delegated to agents:
showroom:file-generator (Sonnet) — generates one AsciiDoc file, runs in parallel for new labsshowroom:module-reviewer (Sonnet) — quality check on generated filesThe orchestrator handles: argument parsing, repo detection, planning, agent spawning, nav merge, delivery.
See @showroom/docs/SKILL-COMMON-RULES.md for AsciiDoc rules, version pinning, image conventions, and navigation format.
If ph_payload is present in the invocation, skip ALL interactive questions and run headless. Return structured JSON.
ph_payload:
target_dir: content/modules/ROOT/pages/
mode: new | continue
previous_module: 03-module-01-pipelines.adoc # continue mode only
spec:
lab_name: OpenShift Pipelines Workshop
audience: intermediate
learning_objectives: [Deploy a pipeline, Configure triggers, Monitor builds]
business_scenario: ACME Corp needs to modernize their CI/CD pipeline
duration: 90min
module_outline: |
Module 1: Pipeline setup (~30 min)
Module 2: Triggers (~30 min)
Module 3: Monitoring (~30 min)
env:
ocp_version: "4.18"
attributes: {user: user1, password: openshift}
Headless return (JSON only, no prose):
{
"files_created": ["index.adoc", "01-overview.adoc", "02-details.adoc", "03-module-01-pipelines.adoc"],
"nav_updated": true,
"quality": {"critical": 0, "high": 0, "warnings": 2},
"warnings": ["Module has only 1 exercise, recommend adding more"]
}
/create-lab # interactive, asks all questions
/create-lab <directory> # specify target directory
/create-lab <directory> --new # new lab, skip mode question
/create-lab <directory> --continue <module> # continue from module
Validate directory exists. If empty: tell user to clone nookbag template first:
git clone https://github.com/rhpds/showroom_template_nookbag <repo-name>
Never suggest showroom-nookbag (hyphens) — always showroom_template_nookbag (underscores).
If not set by arguments:
Are you:
1. Starting a NEW lab (creates index + overview + details + first module)
2. Adding a module to an EXISTING lab
Detect content type from existing files (no question):
=== Verify sections or numbered exercises → WorkshopFor NEW lab — ask as one grouped form:
Let's plan your workshop. Answer all at once or skip any you're unsure about:
Lab name:
Target audience (e.g. Developers, SREs, Platform Engineers):
Experience level (Beginner / Intermediate / Advanced):
Main learning goal (what can learners DO when finished?):
Learning outcomes (list 3-4 skills they'll gain):
Business scenario (company name + challenge, e.g. "ACME Corp needs to modernize CI/CD"):
Duration (e.g. 30min, 1hr, 2hr):
Module breakdown (how many modules, what each covers):
OpenShift version (or leave blank for {ocp_version} placeholder):
Cluster type (multinode / SNO):
Access type (admin / multi-user htpasswd / keycloak):
UserInfo variables (paste from demo.redhat.com → My services → Details → Advanced settings):
Leave blank to use placeholder attributes {user}, {password}, {openshift_console_url}
Reference materials (paste URLs, file paths, or text — leave blank to use templates):
Writing style (optional — skip for standard Red Hat style):
Describe: "conversational, short sentences, active voice, no jargon"
OR paste 1-3 paragraphs of your own writing as an example
OR give a file path: ~/my-showroom/content/modules/ROOT/pages/03-my-module.adoc
Saved profile? Point to: ~/.claude/context/my-writing-style.md
User fills what they know, skips the rest. Orchestrator confirms the plan in one summary block:
📋 Plan confirmed:
Lab: [name] | [audience] | [duration]
Modules: [breakdown]
Environment: OCP [version] | [access type]
References: [N URLs / no references]
Generating files... (running in parallel)
For CONTINUE mode — minimal questions:
Which module are you adding? (title + brief description)
Reference materials for this module? (URLs, files, or blank)
Include troubleshooting section? [Y/n]
Ask Q0–Q3 from @showroom/skills/create-lab/references/showroom-scaffold.md:
Create/update site.yml and ui-config.yml in repo root.
Build FULL_SPEC JSON from the planning form answers.
NEW lab — spawn all files simultaneously:
Task tool:
subagent_type: showroom:file-generator
prompt: |
TARGET_FILE: <repo_path>/content/modules/ROOT/pages/index.adoc
FILE_TYPE: index
FULL_SPEC: <FULL_SPEC JSON>
LAB_TYPE: <ocp|rhel|vm|ai>
CONTENT_TYPE: <workshop|demo>
REPO_PATH: <absolute repo path>
Task tool:
subagent_type: showroom:file-generator
prompt: |
TARGET_FILE: <repo_path>/content/modules/ROOT/pages/01-overview.adoc
FILE_TYPE: overview
FULL_SPEC: <FULL_SPEC JSON>
...
Task tool:
subagent_type: showroom:file-generator
prompt: |
TARGET_FILE: <repo_path>/content/modules/ROOT/pages/02-details.adoc
FILE_TYPE: details
FULL_SPEC: <FULL_SPEC JSON>
...
Task tool:
subagent_type: showroom:file-generator
prompt: |
TARGET_FILE: <repo_path>/content/modules/ROOT/pages/03-module-01-<slug>.adoc
FILE_TYPE: module
FULL_SPEC: <FULL_SPEC JSON>
...
All four run concurrently. Wait for all to return JSON.
CONTINUE mode — single agent, sequential:
Task tool:
subagent_type: showroom:file-generator
prompt: |
TARGET_FILE: <repo_path>/content/modules/ROOT/pages/<next-module>.adoc
FILE_TYPE: module
FULL_SPEC: <FULL_SPEC JSON>
PREVIOUS_MODULE: <path to previous .adoc>
REPO_PATH: <absolute repo path>
Spawn showroom:module-reviewer on each generated file:
Task tool:
subagent_type: showroom:module-reviewer
prompt: |
MODULE_FILE: <path to generated .adoc>
CONTENT_TYPE: <workshop|demo>
LAB_TYPE: <ocp|rhel|vm|ai>
SHARED_CONTEXT: {"module_order": [...], "defined_attributes": {...}, "first_use_map": {}, "lab_type": "ocp", "content_type": "workshop"}
REPO_PATH: <absolute repo path>
is_first_module: <true if overview>
is_conclusion: false
Collect findings. If Critical or High issues found, fix inline before delivering.
Merge nav_entry values from each file-generator JSON output.
Read existing content/modules/ROOT/nav.adoc. Insert new entries in correct order. Write back.
Confirm: ✅ nav.adoc updated with [N] new entries.
Human mode:
✅ Files created:
index.adoc (247 words)
01-overview.adoc (312 words)
02-details.adoc (198 words)
03-module-01-pipeline-setup.adoc (1,340 words, 2 exercises)
✅ nav.adoc updated
Quality: 0 Critical, 0 High, 2 Warnings
- W1: Module has only 1 exercise — consider adding a second
- W2: [source,bash] found — run /verify-content E.3a fix when ready
Next: Add more modules with /create-lab --continue, or verify the full lab with /verify-content
Headless mode: return JSON from Phase 2's ph_payload schema.
When all modules are complete and user asks for the conclusion:
Task tool:
subagent_type: showroom:file-generator
prompt: |
FILE_TYPE: conclusion
FULL_SPEC: <FULL_SPEC JSON with all module summaries>
...
See @showroom/skills/create-lab/references/conclusion-template.md for conclusion structure.
/showroom:verify-content — full quality review after content is created/showroom:create-demo — presenter-led demo content/ftl:rhdp-lab-validator — write E2E solve/validate automationtools
Writes validate.yml playbooks using the validation_check Ansible plugin. Takes the content-reader task report and solve-writer actions as input, producing checks that verify student progress without manual steps or navigation instructions.
tools
Writes solve.yml playbooks from the structured task report produced by ftl:content-reader. Uses the automation priority ladder (k8s_exec → k8s → uri → wait_for → Playwright) to generate Ansible tasks that replicate what the student does in the lab.
development
Pushes solve.yml and validate.yml to a live RHDP showroom, restarts the pod, and runs the full test cycle (fresh validate → solve → validate again → idempotency check). Reports pass/fail per task with full output for debugging.
tools
AsciiDoc reader agent for the FTL lab validator. Reads a showroom .adoc module file, extracts executable code blocks (role="execute"), classifies each step by automation type, and outputs a structured task report for the solve-writer and validate-writer agents.