Azure Architecture Autopilot
github/awesome-copilot
Designs Azure infrastructure from a natural-language description, or diagrams an existing resource group, then refines the design through conversation and deploys it with Bicep.
Deploy trained robot policies to edge fleets via FluxCD GitOps, image automation, and deployment gating
Install Fleet Deployment
$ npx skills add microsoft/physical-ai-toolchain --skill fleet-deployment -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install microsoft/physical-ai-toolchain fleet-deployment --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/microsoft/physical-ai-toolchain.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/fleet-deployment .claude/skills/fleet-deployment && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "fleet-deployment" agent skill from https://github.com/microsoft/physical-ai-toolchain/tree/main/.github/skills/fleet-deployment into .claude/skills/fleet-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fleet-deployment", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/microsoft/physical-ai-toolchain/tree/main/.github/skills/fleet-deploymentType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add microsoft/physical-ai-toolchain --skill fleet-deployment -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install microsoft/physical-ai-toolchain fleet-deployment --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/physical-ai-toolchain.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.github/skills/fleet-deployment .agents/skills/fleet-deployment && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "fleet-deployment" agent skill from https://github.com/microsoft/physical-ai-toolchain/tree/main/.github/skills/fleet-deployment into .agents/skills/fleet-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fleet-deployment", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add microsoft/physical-ai-toolchain --skill fleet-deployment -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install microsoft/physical-ai-toolchain fleet-deployment --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/physical-ai-toolchain.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.github/skills/fleet-deployment .cursor/skills/fleet-deployment && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "fleet-deployment" agent skill from https://github.com/microsoft/physical-ai-toolchain/tree/main/.github/skills/fleet-deployment into .cursor/skills/fleet-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fleet-deployment", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/microsoft/physical-ai-toolchain.git --path .github/skills/fleet-deployment--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add microsoft/physical-ai-toolchain --skill fleet-deployment -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install microsoft/physical-ai-toolchain fleet-deployment --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/physical-ai-toolchain.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.github/skills/fleet-deployment .gemini/skills/fleet-deployment && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "fleet-deployment" agent skill from https://github.com/microsoft/physical-ai-toolchain/tree/main/.github/skills/fleet-deployment into .gemini/skills/fleet-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fleet-deployment", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install microsoft/physical-ai-toolchain fleet-deploymentInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add microsoft/physical-ai-toolchain --skill fleet-deployment -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/microsoft/physical-ai-toolchain.git skills-src && mkdir -p .github/skills && cp -r skills-src/.github/skills/fleet-deployment .github/skills/fleet-deployment && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "fleet-deployment" agent skill from https://github.com/microsoft/physical-ai-toolchain/tree/main/.github/skills/fleet-deployment into .github/skills/fleet-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fleet-deployment", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add microsoft/physical-ai-toolchain --skill fleet-deployment -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install microsoft/physical-ai-toolchain fleet-deployment --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/physical-ai-toolchain.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.github/skills/fleet-deployment .opencode/skills/fleet-deployment && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "fleet-deployment" agent skill from https://github.com/microsoft/physical-ai-toolchain/tree/main/.github/skills/fleet-deployment into .opencode/skills/fleet-deployment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fleet-deployment", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
fleet-deployment- GitHub stars
- 122
- Token cost
- ~518 tokens
- SKILL.md length
- 156 words
- Files
- 1
- Skills in repo
- 7
- Repo updated
- First seen
- Licence
- MIT
At a glance
Deploy trained robot policies to edge fleets via FluxCD GitOps, image automation, and deployment gating
- Works in 4 steps: Bootstrap FluxCD → Configure image automation → Set up deployment gating → …
- Tasks that involve Deployment
- SKILL.md covers Prerequisites, Deployment Workflow, Key Directories and Specifications
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Fleet Deployment is an agent skill from microsoft/physical-ai-toolchain, published by the product's own GitHub organization. Deploy trained robot policies to edge fleets via FluxCD GitOps, image automation, and deployment gating
Its SKILL.md is about 520 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in DevOps & Cloud, covering Deployment and GitOps. It works with Microsoft Azure. The licence is MIT.
When your agent uses it
- Tasks that involve Deployment
- Tasks that involve GitOps
Example prompts
- “/fleet-deployment”
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 5d38197. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Fleet Deployment loads about 518 tokens when it runs. Until then it costs about 30 tokens; SKILL.md has 156 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from microsoft/physical-ai-toolchain at commit 5d38197, republished under its MIT licence (© microsoft). 156 words, ~518 tokens.
Download SKILL.mdSave it as
.claude/skills/fleet-deployment/SKILL.md (or your agent's skills folder).- name
- fleet-deployment
- description
- Deploy trained robot policies to edge fleets via FluxCD GitOps, image automation, and deployment gating
Fleet Deployment
Deploy trained robot policies to edge robot fleets using FluxCD GitOps pipelines, automated image updates, and deployment gating.
Prerequisites
| Tool | Requirement |
|---|---|
kubectl | Authenticated to target cluster |
flux | FluxCD CLI 2.x |
az CLI | Azure authentication for ACR access |
Deployment Workflow
Step 1 — Bootstrap FluxCD
fleet-deployment/gitops/bootstrap.shInstalls Flux components on the target cluster and configures Git source reconciliation.
Step 2 — Configure image automation
Define ImageRepository, ImagePolicy, and ImageUpdateAutomation resources in fleet-deployment/gitops/image-automation/.
Step 3 — Set up deployment gating
Configure gate criteria in fleet-deployment/gating/ to validate models before rollout.
Step 4 — Deploy to fleet
FluxCD reconciles cluster state from Git. New model images trigger automated manifest updates and gated rollout.
Key Directories
| Directory | Purpose |
|---|---|
fleet-deployment/gitops/ | FluxCD manifests, sources, releases, and cluster overlays |
fleet-deployment/gating/ | Deployment gating service and Kubernetes manifests |
fleet-deployment/inference/ | On-device inference runtime code |
fleet-deployment/examples/ | Example deployment configurations |
fleet-deployment/specifications/ | Domain specification documents |
Specifications
| Document | Description |
|---|---|
| fleet-deployment.specification.md | Domain overview and component contracts |
| gitops.specification.md | FluxCD GitOps architecture |
| gating-service.specification.md | Deployment gating service |
© microsoft, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .github/skills/fleet-deployment of microsoft/physical-ai-toolchain.
Open the folder on GitHubat commit 5d38197
Compare with similar skills
Fleet Deployment next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Fleet Deployment this skillmicrosoft/physical-ai-toolchain | 122 | — | ~518 | Automated safety check: Pass | MIT | |
| Azure Architecture Autopilotgithub/awesome-copilot | 40k | 1 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Aspiremicrosoft/aspire.dev | 196 | 4 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Capacitymicrosoft/GitHub-Copilot-for-Azure | 255 | 2 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Azure AI Agent App DeploymentAzure-Samples/get-started-with-ai-agents | 374 | — | ~4.7k | Automated safety check: Notes | MIT | |
| Aspire MonitoringCommunityToolkit/Aspire | 629 | — | ~3.5k | Automated safety check: Pass | MIT |
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Related
Works with
Categories
Questions about Fleet Deployment
What does Fleet Deployment do?
Deploy trained robot policies to edge fleets via FluxCD GitOps, image automation, and deployment gating. Fleet Deployment is an agent skill from microsoft/physical-ai-toolchain, published by the product's own GitHub organization.
When should I use Fleet Deployment?
Fleet Deployment fits situations like: tasks that involve Deployment; tasks that involve GitOps.
How do I install Fleet Deployment in Claude Code?
Run `npx skills add microsoft/physical-ai-toolchain --skill fleet-deployment -a claude-code`. Or copy the skill folder (.github/skills/fleet-deployment in microsoft/physical-ai-toolchain) into .claude/skills/fleet-deployment in your project. Claude Code loads it when a task matches its description.
How do I install Fleet Deployment in Codex?
Run `npx skills add microsoft/physical-ai-toolchain --skill fleet-deployment -a codex`. Or copy the skill folder (.github/skills/fleet-deployment in microsoft/physical-ai-toolchain) into .agents/skills/fleet-deployment in your project. Codex loads it when a task matches its description.
Can I use Fleet Deployment in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft/physical-ai-toolchain --skill fleet-deployment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fleet-deployment, .gemini/skills/fleet-deployment, .github/skills/fleet-deployment and .opencode/skills/fleet-deployment in your project.
What does Fleet Deployment need to run?
SKILL.md names no scripts, command-line tools or credentials: Fleet Deployment is instructions for the agent only.
Does Fleet Deployment access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Fleet Deployment safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Fleet Deployment use?
Fleet Deployment is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Fleet Deployment use?
About 518 tokens (SKILL.md is roughly 2.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Fleet Deployment?
Skills that share tags, products or a category with Fleet Deployment: Azure Architecture Autopilot (github/awesome-copilot, 40k stars), Aspire (microsoft/aspire.dev, 196 stars), Capacity (microsoft/GitHub-Copilot-for-Azure, 255 stars) and Azure AI Agent App Deployment (Azure-Samples/get-started-with-ai-agents, 374 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Fleet Deployment?
microsoft (a GitHub organization, an official publisher) maintains it in microsoft/physical-ai-toolchain, which has 122 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on October 6, 2026.
Source: microsoft/physical-ai-toolchain on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.