// Initialize a new customer engagement. Creates the engagement directory structure, gathers core engagement metadata through a structured interview, and writes the initial CONTEXT.md that all subsequent skills will build upon. Run this first — it's the foundation everything else reads from.
Collect system information by running a local discovery script. Demonstrates how a skill can execute a binary or script behind the scenes to gather data that feeds into the engagement assessment. Use when the architect runs /assess-app-portfolio, mentions "app assessment", "system info", or "collect system data".
Generate a customer-facing executive presentation from all engagement artifacts. Reads CONTEXT.md and all assessment/discovery reports to produce a polished deliverable deck. Supports output as Red Hat Quick Deck (HTML), PPTX, or both. Use when the architect runs /build-deliverable-deck, says "build the deck", "create the presentation", "executive readout", "customer deliverable", or "put together the final slides".
Conduct a structured infrastructure discovery interview for a customer engagement. Walks the architect through compute, networking, storage, identity, CI/CD, and operational tooling topics. Produces a discovery report and updates CONTEXT.md. Use when the architect runs /discover-infrastructure, says "let's do discovery", "map the infrastructure", or "what's in their environment".
| name | setup |
| description | Initialize a new customer engagement. Creates the engagement directory structure, gathers core engagement metadata through a structured interview, and writes the initial CONTEXT.md that all subsequent skills will build upon. Run this first — it's the foundation everything else reads from. |
This skill bootstraps a new customer engagement by gathering essential metadata and creating the engagement workspace. It produces the CONTEXT.md file that every downstream skill depends on.
/setup in Claude Code or OpenCodeengagements/ directory has no customer subdirectories yetConduct a structured interview with the architect. Ask these questions conversationally — don't dump them all at once. Group related questions and adapt based on answers.
Required Fields (must have before proceeding):
| Field | Question | Example |
|---|---|---|
customer_name | "What's the customer name?" | Acme Federal |
customer_slug | Auto-generate from name (kebab-case) | acme-federal |
engagement_type | "What type of engagement is this?" | See engagement types below |
architect_name | "Who's the lead architect?" | Todd Wardzinski |
engagement_dates | "What are the start and target end dates?" | 2026-04-01 → 2026-06-30 |
executive_sponsor | "Who's the customer executive sponsor?" | Jane Smith, CTO |
Engagement Types (offer these as options):
Optional Fields (ask but don't block on):
| Field | Question |
|---|---|
clearance_level | "Any clearance requirements? (Unclassified, CUI, Secret, TS/SCI)" |
environment_type | "Connected, limited connectivity, or air-gapped?" |
team_members | "Who else is on the engagement team?" |
customer_industry | "What sector? (Federal Civilian, DoD, IC, SLED, Critical Infrastructure)" |
existing_rh_footprint | "Any existing Red Hat products in the environment?" |
key_constraints | "Any known constraints? (budget, timeline, compliance, legacy dependencies)" |
success_criteria | "What does success look like for this engagement?" |
Once you have the required fields, create the directory structure:
CUSTOMER_SLUG="<customer_slug>"
mkdir -p "engagements/${CUSTOMER_SLUG}"/{discovery,assessments,deliverables}
Set up the repo's shared Git hooks to prevent accidental pushes of customer-sensitive data:
git config core.hooksPath .claude/skills/setup/hooks
This activates the pre-push hook that blocks all pushes to remote. The hook is bundled with this skill under .claude/skills/setup/hooks/.
Generate the initial CONTEXT.md at engagements/<slug>/CONTEXT.md using this template:
# Engagement Context: <Customer Name>
> This file is the living memory for this engagement. Every skill reads from and
> appends to this file. Do not manually edit unless correcting an error.
## Engagement Metadata
- **Customer:** <customer_name>
- **Type:** <engagement_type>
- **Lead Architect:** <architect_name>
- **Dates:** <start_date> → <end_date>
- **Executive Sponsor:** <executive_sponsor>
- **Clearance:** <clearance_level or "Unclassified">
- **Environment:** <environment_type or "Connected">
- **Industry:** <customer_industry or "Not specified">
- **Existing RH Footprint:** <existing_rh_footprint or "Unknown — to be discovered">
## Team
- <architect_name> (Lead Architect)
<additional team members if provided>
## Constraints
<key_constraints or "None identified yet">
## Success Criteria
<success_criteria or "To be defined during discovery">
## Engagement Log
### <today's date> — Engagement Initialized
- Engagement workspace created by <architect_name>
- Type: <engagement_type>
- Status: **Discovery phase**
---
<!-- Skills append their findings below this line -->
Create or update the repo-level .gitignore to protect sensitive engagement data:
# Engagement artifacts that should never be pushed to shared remotes
engagements/*/discovery/*.sensitive
engagements/*/discovery/*.classified
# OS artifacts
.DS_Store
Thumbs.db
# Editor artifacts
*.swp
*.swo
*~
After creating the workspace, confirm what was created and recommend the logical next skill:
✅ Engagement initialized: <customer_name>
📁 Workspace: engagements/<slug>/
📄 Context: engagements/<slug>/CONTEXT.md
Recommended next steps based on engagement type:
Next-step recommendations by engagement type:
| Engagement Type | Recommended Next Skill |
|---|---|
| Application Modernization | /discover-infrastructure then /assess-app-portfolio |
| AI/ML Enablement | /discover-infrastructure then /assess-app-portfolio |
| Platform Assessment | /discover-infrastructure then /assess-app-portfolio |
| Security & Compliance | /discover-infrastructure with security focus |
| Infrastructure Modernization | /discover-infrastructure |
| Custom | /discover-infrastructure (always a good starting point) |
<slug> already exists. Do you want to resume it, or create a new one with a different name?"## Known Gaps section.Architect: /setup
Agent: Let's get this engagement started. What's the customer name?
Architect: Acme Federal Services
Agent: Got it — Acme Federal Services. What type of engagement is this?
1. Application Modernization
2. AI/ML Enablement
3. Platform Assessment
4. Security & Compliance
5. Infrastructure Modernization
6. Custom
Architect: 2 - AI/ML Enablement
Agent: Who's the lead architect for this engagement?
Architect: Me — Todd Wardzinski
Agent: What are the start and target end dates?
Architect: Starting next week, targeting end of Q2
Agent: And who's the customer executive sponsor?
Architect: Deputy Director of IT, Mark Johnson
Agent: A few more optional details that'll help downstream —
Any clearance requirements?
Architect: TS/SCI
Agent: Environment type — connected, limited connectivity, or air-gapped?
Architect: Air-gapped
Agent: Any existing Red Hat products in the environment?
Architect: RHEL 8 across the board, some Ansible Tower
Agent: ✅ Engagement initialized: Acme Federal Services
📁 Workspace: engagements/acme-federal-services/
📄 Context: engagements/acme-federal-services/CONTEXT.md
Since this is an AI/ML Enablement engagement in an air-gapped TS/SCI environment,
I'd recommend starting with `/discover-infrastructure` to map the compute and
data landscape, with special attention to GPU resources and data classification levels.