"device", "laptop", "endpoint"?
get_device / list_user_devices
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Device Fleet Management
Endpoint management for AI agents — device health, security posture, compliance checks, diagnostics, and remediation via mcp-device-management (Intune/Jamf/Fleet/Kandji).
What this skill teaches
A reusable playbook for a specific kind of work.
An MCP server tells an agent which actions are available. A skill adds the judgment around those actions: how to recognize the job, which sequence to follow, what to avoid, and how to decide that the result is complete.
Manage device fleets — get device info, check security posture, list applications, collect diagnostics, run health checks, and create remediation tasks. Use when checking device health, auditing security posture, listing installed apps, collecting diagnostics, or remediating compliance issues.
Architecture
How Device Fleet Management guides an ADK-Rust agent.
The skill stays readable and portable because it contains instructions rather than service credentials or business data. ADK-Rust supplies it to the agent, the agent chooses from its reviewed tool boundary, and the connected MCP server performs the authenticated operation.
01
User request
The agent receives a goal expressed in ordinary language.
02
Device Fleet Management skill
Matches intent, supplies the decision guide, and narrows the tool boundary.
03
ADK-Rust agent
Plans the workflow and streams each meaningful step through the runtime.
04
mcp-device-management
Executes authenticated operations against the system that owns the capability.
05
Verified result
The skill's completion rules shape the evidence returned to the user.
Decision guide
How the agent turns a request into the right action.
These routes come directly from the skill instructions. They help the model recognize intent and select a focused tool or workflow instead of improvising across the entire capability surface.
"security", "posture", "compliant"?
get_security_posture
"apps", "installed", "software"?
list_applications
"health", "check", "status"?
run_health_check / get_system_stats
"diagnose", "troubleshoot"?
collect_diagnostics / list_processes / get_network_info
"fix", "remediate"?
create_remediation
Proven workflows
Repeatable sequences for useful outcomes.
A workflow joins several tool calls into a task the user actually recognizes. The skill explains the sequence and the intended result while ADK-Rust streams the agent's progress through the shared runtime.
011-2 calls
Security Posture
Compliance check against policy
022 calls
Health Check
System stats + diagnostics
031 calls
Remediation
Create fix task for violations
042-3 calls
Fleet Report
Compliance % across all devices
Tool boundary
The skill may use 10 documented tools.
This allowlist is declared by the skill. It keeps the agent focused on the actions needed for this job while mcp-device-management retains responsibility for authentication, validation, and the connected system.
get_device
list_user_devices
get_security_posture
list_applications
collect_diagnostics
run_health_check
create_remediation
get_system_stats
list_processes
get_network_info
Working rules
What the agent should do.
- Check security posture before granting access
- Flag non-compliant devices (missing encryption, outdated OS)
- Collect diagnostics before escalating hardware issues
- Verify device ownership before pushing configs
Operating boundaries
What the agent should avoid.
- NEVER wipe devices without explicit human approval
- Don't push configs to personal (BYOD) devices without consent
- Don't expose device data beyond need-to-know
Install and connect
Add the skill beside the capability it expects.
Install the repository where your ADK-Rust skill loader can discover it, connect mcp-device-management, and confirm the declared tools are available before asking the agent to use the workflow.
Install the skill
git clone https://github.com/zavora-ai/skill-device-fleet-management.git \
~/.skills/skills/device-fleet-managementADK-Rust loading shape
let skills = SkillLoader::from_dir("~/.skills/skills").await?;
let skill = skills.load("device-fleet-management").await?;
let agent = LlmAgentBuilder::new("agent")
.instruction(skill.instructions())
.tools(skill.allowed_tools(toolset)?)
.build()?;The repository's compatibility statement: Requires mcp-device-management server connected.
Official documentation
Read the complete skill package.
The repository remains authoritative for its exact instructions, examples, helper scripts, assets, MCP requirements, license, and later updates.
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Source record
Repository metadata for this skill entry.
- License
- Apache-2.0
- Allowed tools
- 10
- References
- 3
- Revision
- fd4a7ac04886
- Updated
- May 31, 2026