Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add davistroy/claude-marketplace --skill fleet-healthgit clone --depth 1 https://github.com/davistroy/claude-marketplaceWrote 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/davistroy/claude-marketplace/fleet-health)<a href="https://agentmods.dev/skills/davistroy/claude-marketplace/fleet-health"><img src="https://agentmods.dev/badge/skills/davistroy/claude-marketplace/fleet-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.
<a href="https://agentmods.dev/skills/davistroy/claude-marketplace/fleet-health"><img src="https://agentmods.dev/badge/skills/davistroy/claude-marketplace/fleet-health.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00126 | $0.03062 |
| Opus 5 | $0.00063 | $0.01531 |
| Sonnet 5 | $0.00025 | $0.00612 |
| Haiku 4.5 | $0.00013 | $0.00306 |
Grade B, and why
fleet-health scanned grade B with 2 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 8d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo_scoped: true # `sudo -n docker ...` works; `sudo cat`/`sudo ls` do NOT — use plain cat/ls or docker's own output Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
description: One-shot, read-only health snapshot across the personal fleet (DGX Spark, Jetson Orin Nano, homeserver, bond, obvm). Checks uptime, load, disk, memory, and each machine's key inference/service endpoints over How it starts
The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fleet Health
Fast, read-only health snapshot across all 5 machines in the personal fleet. Unlike spark-audit / jetson-audit (deep, single-machine, best-practices audits), this skill is a wide, shallow, fleet-wide pulse check — designed to answer "is everything up?" in well under a minute, with a final line a headless cron job can grep for.
This skill reads the live system. It never modifies it.
No paths: activation is configured — this skill runs only on explicit invocation ("fleet status", "morning brief", "is the spark available", etc.). Since it never auto-triggers, no loop guard is needed.
Fleet Config
ssh:
key: "~/.ssh/id_claude_code"
opts: "-o ConnectTimeout=5 -o BatchMode=yes"
user: "claude"
curl:
opts: "-sf -m 5"
fleet:
- name: "DGX Spark"
host: "spark.k4jda.net"
lan_ip: "192.168.10.33"
role: "LLM inference (vLLM) — chat, embeddings, NER"
gpu: nvidia-smi
key_ports:
8000: { service: "spark-llm (Qwen3.6-35B-A3B-FP8)", check: "GET /v1/models, expect data[0].id == spark-llm" }
8001: { service: "qwen3-embedding-4b", check: "GET /v1/models, expect data[0].id == qwen3-embedding-4b" }
8002: { service: "GLiNER NER", check: "GET /health, expect status == ok" }
- name: "Jetson Orin Nano"
host: "jetson.k4jda.net"
lan_ip: "192.168.10.58"
role: "Edge LLM inference (llama.cpp), single-process mode-switched"
gpu: tegrastats # NO nvidia-smi on this box — do not attempt it
key_ports:
8080: { service: "active llama-server mode (default qwen35)", check: "GET /health, expect status == ok" }
8081: { service: "embedding mode (Qwen3-Embedding-4B)", check: "see Known States — U2: expected DOWN unless mode.txt=embedding" }
- name: "Homeserver"
host: "homeserver.k4jda.net"
role: "Docker host (Unraid) — ~55 containers, Prometheus/Grafana/Alertmanager stack"
sudo_scoped: true # `sudo -n docker ...` works; `sudo cat`/`sudo ls` do NOT — use plain cat/ls or docker's own output
use_wget_locally: true # curl is not reliably available ON the homeserver itself — use wget when SSH'd in
- name: "Bond"
host: "bond.k4jda.net"
role: "General purpose"
- name: "open-brain-vm (obvm)"
host: "obvm.k4jda.net"
role: "T2 Claude CLI batch, Python, ops"
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.
- 8d ago First seen · 173 lines · 126 tokens per session scan B c91c33481ba8
fleet-health is a skill published in the GitHub repository davistroy/claude-marketplace (5 stars, last pushed 5d ago), licensed MIT. It adds 126 tokens to every session and 3,062 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 2 findings (asks for root, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.
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