fleet-onboard
Run the fleet onboarding wizard — checks what's configured, what's missing, and guides new users through setup
Skill by supportersimulator
Chalk Labs
Need help deploying fleet-onboard?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/supportersimulator-fleet-onboard
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/fleet-onboard
What's inside
- Skill name
fleet-onboard- Description
- Run the fleet onboarding wizard — checks what's configured, what's missing, and guides new users through setup
- License
- MIT
- Instructions
- 55 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Fleet Onboard
Interactive onboarding wizard for new fleet nodes. Runs 10 diagnostic checks and generates a step-by-step setup guide.
## Usage
```bash
# Render the setup guide (markdown)
python3 -m multifleet.onboarding
# JSON output for automation
python3 -m multifleet.onboarding --json
# Override node ID
python3 -m multifleet.onboarding --node-id mac4
```
### Via MCP tool
Use the `fleet_onboard` MCP tool to get onboarding status and guide in one call.
### Via Python
```python
from multifleet.onboarding import OnboardingWizard
wiz = OnboardingWizard()
status = wiz.check_all()
print(f"Ready: {status['ready']} — {status['progress_pct']:.0f}%")
print(wiz.render_guide())
```
## Checks
| # | Check | Required | What it verifies |
|---|-------|----------|-----------------|
| 1 | python | Yes | python3 in PATH and working |
| 2 | nats | Yes | NATS server reachable on port 4222 |
| 3 | daemon | Yes | Fleet daemon responding on port 8855 |
| 4 | keychain | Yes | HMAC key stored in macOS Keychain |
| 5 | superset | No | Superset API key configured |
| 6 | config | Yes | .multifleet/config.json exists and parses |
| 7 | ssh | No | SSH keys loaded in agent |
| 8 | probes | No | Probe modules present |
| 9 | surgeons | No | 3-surgeons MCP plugin installed |
| 10 | skills | No | Skills directory populated |
## When to use
- Setting up a brand new machine in the fleet
- After a fresh OS install or environment reset
- Debugging "why can't this node communicate?"
- Verifying a node is fully operational before assigning workFrom supportersimulator/multi-fleet, MIT.
More from supportersimulator/multi-fleet
- 0.440score
fleet-rebuttal
supportersimulator
Cross-machine rebuttal protocol — the 4-phase cycle where machines produce verdicts, critique each other, and converge on a chief decision
SkillDFreshness: D★ 2Claude Code +9 - 0.440score
fleet-race
supportersimulator
Competitive branch racing — 3 machines solve the same problem in isolated worktrees, then propose/rebut/converge to the strongest solution
SkillDFreshness: D★ 2Claude Code +9 - 0.440score
fleet-healer
supportersimulator
Invariance layer — spawns background agents that automatically heal broken fleet communication channels until all reach ideal state
SkillDFreshness: D★ 2Claude Code +9 - 0.436score
fleet-dispatch
supportersimulator
Remote worker dispatch — send tasks to fleet nodes and track results with priority routing
SkillDFreshness: D★ 2Claude Code +9 - 0.436score
fleet-repair
supportersimulator
4-level repair escalation for broken fleet channels — notify, guide, assist, remote
SkillDFreshness: D★ 2Claude Code +9 - 0.436score
fleet-chain
supportersimulator
Chain orchestration — multi-step task dependencies across fleet nodes with automatic sequencing
SkillDFreshness: D★ 2Claude Code +9 - 0.436score
fleet-check
supportersimulator
Run the full 7-channel communication test — verifies every delivery path to a target node
SkillDFreshness: D★ 2Claude Code +9 - 0.436score
fleet-idle
supportersimulator
Productive idle protocol — automatic work discovery and suggestion when fleet nodes are idle
SkillDFreshness: D★ 2Claude Code +9 - 0.436score
fleet-liaison
supportersimulator
Interact with the fleet liaison agent — check status, read batched messages, escalate outbound, pause/resume monitoring
SkillDFreshness: D★ 2Claude Code +9 - 0.436score
fleet-security
supportersimulator
HMAC message signing, replay prevention, peer validation, and session gold sanitization
SkillDFreshness: D★ 2Claude Code +9 - 0.436score
fleet-send
supportersimulator
Send a message to another machine in the fleet — context, task, alert, or broadcast with 7-priority fallback delivery
SkillDFreshness: D★ 2Claude Code +9 - 0.436score
fleet-status
supportersimulator
Quick fleet health check — who's online, who's idle, what's everyone working on
SkillDFreshness: D★ 2Claude Code +9
Signals
- Stars
- 2
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Apr 8, 2026 (7 months ago)
- Last release
- Apr 18, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from supportersimulator
- 0.440score
fleet-healer
supportersimulator
Invariance layer — spawns background agents that automatically heal broken fleet communication channels until all reach ideal state
SkillDFreshness: D★ 2Claude Code +9 - 0.440score
fleet-rebuttal
supportersimulator
Cross-machine rebuttal protocol — the 4-phase cycle where machines produce verdicts, critique each other, and converge on a chief decision
SkillDFreshness: D★ 2Claude Code +9 - 0.440score
fleet-race
supportersimulator
Competitive branch racing — 3 machines solve the same problem in isolated worktrees, then propose/rebut/converge to the strongest solution
SkillDFreshness: D★ 2Claude Code +9 - 0.436score
fleet-check
supportersimulator
Run the full 7-channel communication test — verifies every delivery path to a target node
SkillDFreshness: D★ 2Claude Code +9 - 0.436score
fleet-dispatch
supportersimulator
Remote worker dispatch — send tasks to fleet nodes and track results with priority routing
SkillDFreshness: D★ 2Claude Code +9 - 0.436score
fleet-chain
supportersimulator
Chain orchestration — multi-step task dependencies across fleet nodes with automatic sequencing
SkillDFreshness: D★ 2Claude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get fleet-onboard running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
fleet-onboard skill. Agent Mart. https://agentmart.dev/skills/supportersimulator-fleet-onboard (last updated 2026-10-24)