A LogicMonitor device health report that checks metrics, anomalies, alerts, availability, and the device's place in the monitored network.

Use it to check a device by ID or name, review its data sources and status, and investigate possible monitoring or availability problems.

It gathers the main signs of a device's condition in one structured report, so you do not have to inspect each monitoring area separately.

How ryanmat/mcp-server-logicmonitor configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to ryanmat/mcp-server-logicmonitor. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/ryanmat/mcp-server-logicmonitor/main/.claude/skills/lm-health/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/ryanmat/mcp-server-logicmonitor

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/ryanmat/mcp-server-logicmonitor/lm-health/github.svg)](https://agentmods.dev/skills/ryanmat/mcp-server-logicmonitor/lm-health)

Your own site

<a href="https://agentmods.dev/skills/ryanmat/mcp-server-logicmonitor/lm-health"><img src="https://agentmods.dev/badge/skills/ryanmat/mcp-server-logicmonitor/lm-health/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/ryanmat/mcp-server-logicmonitor/lm-health"><img src="https://agentmods.dev/badge/skills/ryanmat/mcp-server-logicmonitor/lm-health.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,297 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00027	$0.01297
Opus 5.5	$0.00011	$0.00519
Sonnet 5.5	$0.00005	$0.00259
Haiku 4.5	$0.00003	$0.00130

Measured 2mo ago against content hash 152720a835a5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

lm-health scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/lm-health/SKILL.md · 184 lines

How it starts

The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LogicMonitor Device Health Check

You are a device health analyst for LogicMonitor. Your job is to run a comprehensive health check on a specific device and produce a structured report covering metrics, anomalies, alerts, availability, and topology context.

Argument Parsing

The user must provide a device identifier:

Numeric value — Treat as a device ID
String value — Treat as a device name (displayName filter)

If no argument is provided, ask the user which device to check.

Workflow

Execute these steps in order. Present findings incrementally.

Step 1: Device Resolution

Resolve the device to a confirmed ID.

If numeric: call get_device with the ID directly.
If string: call get_devices with a displayName~"<name>" filter.
- If exactly one match, proceed.
- If multiple matches, list them and ask the user to pick one.
- If zero matches, try a broader name~"<name>" filter. If still no match, report the device was not found and stop.

Capture: device ID, display name, device type, host group(s), collector ID, status.

Step 2: Datasource Inventory

Call get_device_datasources for the resolved device ID.

Categorize datasources into buckets:

CPU — datasources with names containing CPU, Processor
Memory — datasources with names containing Memory, RAM, Swap
Disk — datasources with names containing Disk, Storage, Volume, Filesystem
Network — datasources with names containing Interface, Network, Ethernet
Other — everything else

Present a count per category and flag any datasources in alert state.

Step 3: Core Metrics

For each category that has datasources (CPU, Memory, Disk, Network):

Call get_device_instances to list instances for the datasource.
Call get_device_data for the top instance(s) to get recent metric values.

Present key metrics:

CPU: utilization %, load average
Memory: used %, available
Disk: used %, free space, I/O
Network: throughput in/out, errors, discards

Read the full file on GitHub · 184 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 184 lines · 27 tokens per session scan A 152720a835a5

Subscribe to this mod's changes

lm-health is a skill published in the GitHub repository ryanmat/mcp-server-logicmonitor (1 stars, last pushed 7d ago), licensed MIT. It adds 27 tokens to every session and 1,297 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Analytics and metrics DevOps and cloud

lm-health next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
lm-healthryanmat/mcp-server-logicmonitor	Skill	1	7d ago	MIT	A	27	Claude Code
imagegenopenai/codex	Skill	133k	yesterday	Apache-2.0	A	113	Codex
playwright-climicrosoft/playwright	Skill	99k	yesterday	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	4d ago	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	313k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	103	Claude Code

mcp-server-logicmonitor: Skill for Claude Code