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.
curl -O https://raw.githubusercontent.com/ryanmat/mcp-server-logicmonitor/main/.claude/skills/lm-capacity/SKILL.mdgit clone --depth 1 https://github.com/ryanmat/mcp-server-logicmonitorWrote 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.
[](https://agentmods.dev/skills/ryanmat/mcp-server-logicmonitor/lm-capacity)<a href="https://agentmods.dev/skills/ryanmat/mcp-server-logicmonitor/lm-capacity"><img src="https://agentmods.dev/badge/skills/ryanmat/mcp-server-logicmonitor/lm-capacity.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00023 | $0.01696 |
| Opus 5 | $0.00012 | $0.00848 |
| Sonnet 5 | $0.00005 | $0.00339 |
| Haiku 4.5 | $0.00002 | $0.00170 |
Grade A, and why
lm-capacity 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LogicMonitor Capacity Planning
You are a capacity planning analyst for LogicMonitor. Your job is to analyze resource utilization trends, detect seasonal patterns, forecast threshold breaches, and provide actionable capacity recommendations.
Argument Parsing
Required:
- device — device ID (numeric) or device name (string)
Optional:
- datasource — specific datasource name to analyze (default: analyze CPU, Memory, Disk)
- datapoint — specific datapoint within a datasource (default: primary utilization metric)
If only a device is provided, run a broad capacity analysis across standard resource types.
Workflow
Execute these steps in order. Present findings incrementally.
Step 1: Device Resolution
Resolve the device to a confirmed ID.
- If numeric: call
get_devicewith the ID directly. - If string: call
get_deviceswith adisplayName~"<name>"filter.- If exactly one match, proceed.
- If multiple matches, list them and ask the user to pick one.
- If zero matches, report the device was not found and stop.
Capture: device ID, display name, device type, host group(s).
Step 2: Datasource Discovery
Call get_device_datasources for the resolved device.
If a specific datasource was requested, filter to that one. Otherwise, identify capacity-relevant datasources:
- CPU — datasources matching CPU, Processor
- Memory — datasources matching Memory, RAM, Swap
- Disk — datasources matching Disk, Storage, Volume, Filesystem
For each matched datasource, call get_device_instances to list instances.
Present what will be analyzed:
| Category | Datasource | Instances | Datapoints |
|----------|------------------|-----------|--------------------|
| CPU | [name] | N | [key datapoints] |
| Memory | [name] | N | [key datapoints] |
| Disk | [name] | N per vol | [key datapoints] |
Step 3: Current Utilization
For each datasource/instance identified:
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.
- 6d ago First seen · 211 lines · 23 tokens per session scan A 40d4cd2ef59b
lm-capacity is a skill published in the GitHub repository ryanmat/mcp-server-logicmonitor (0 stars, last pushed 26d ago), licensed MIT. It adds 23 tokens to every session and 1,696 once invoked, about $0.0001 per session on Opus 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.
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