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 agentmods add skills/frontier-ai-next/mgarlbot/ops_reverse_proxynpx skills add frontier-ai-next/mgarlbot --skill ops_reverse_proxygit clone --depth 1 https://github.com/frontier-ai-next/mgarlbotWrote 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/frontier-ai-next/mgarlbot/ops_reverse_proxy)<a href="https://agentmods.dev/skills/frontier-ai-next/mgarlbot/ops_reverse_proxy"><img src="https://agentmods.dev/badge/skills/frontier-ai-next/mgarlbot/ops_reverse_proxy.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 | $0.00038 | $0.01110 |
| Opus 5 | $0.00019 | $0.00555 |
| Sonnet 5 | $0.00008 | $0.00222 |
| Haiku 4.5 | $0.00004 | $0.00111 |
Grade A, and why
ops_reverse_proxy scanned grade A with 1 finding 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 4d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
Post-deploy check: `curl -sS -I http://<host>/` (and `Host:` if needed), not `https://` by default. How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Operator stack today: HTTP-only on the reverse proxy
Treat the edge (Traefik / Nginx / frp) as plain HTTP (port 80 or frp equivalent). Do not add TLS, websecure, tls=true, certresolver, or require Let’s Encrypt until existing projects on the same VPS clearly terminate HTTPS or the user explicitly asks for HTTPS.
Post-deploy check: curl -sS -I http://<host>/ (and Host: if needed), not https:// by default.
Inspect first, then copy the pattern
Before writing a new docker-compose.yml, Traefik labels, or an Nginx server {}, understand what already runs on the target server and how other projects are wired. Otherwise you get a second incompatible stack (wrong Docker network, wrong entrypoint).
Remote VPS work uses vps_host_ssh:
ssh -F /data/.ssh/config vps 'COMMAND'
(If the bot runs without Docker but with HOST SHELL, the same SSH from the configured host is fine.)
Step 1 — what serves traffic (HTTP first)
- Containers:
docker ps --format 'table {{.Names}}\t{{.Image}}\t{{.Ports}}' - Traefik: names like
traefik,proxy, imagetraefik:*. If present, sample labels from a routed service:docker inspect SERVICE_NAME --format '{{json .Config.Labels}}' | head -c 12000- Check entrypoints: if everything is
web/:80, new services stay HTTP-only. If you seewebsecure+tls.certresolver, copy TLS like the neighbors.
- Host Nginx:
test -d /etc/nginx/sites-enabled && ls -1 /etc/nginx/sites-enabled || trueand optionallygrep -R listen /etc/nginx/sites-enabled/ 2>/dev/null | head -30— if onlylisten 80, do not addlisten 443 sslwithout a user request and certs. - frp:
pgrep -a frpc || true; common paths~/frp/frpc.toml,/etc/frp/frpc.toml,/opt/frp/frpc.toml— read-only. For HTTP prefertype = httpandcustomDomains; do not switch tohttpswithout a clear need.
Step 2 — where other compose projects live
Avoid aggressive find /:
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.
- 4d ago First seen · 68 lines · 38 tokens per session scan A 581f4ec4e5e1
ops_reverse_proxy is a skill published in the GitHub repository frontier-ai-next/mgarlbot (17 stars, last pushed 28d ago), licensed MIT. It adds 38 tokens to every session and 1,110 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
network-rca
Kubernetes network root cause analysis skill powered by Kubeshark MCP. Use this skill whenever the user wants to investigate past incidents, perform retrospective traffic analysis, take or manage traffic snapshots, extract PCAPs, dissect L7 API calls from historical captures, compare traffic patterns over time, detect…
ecspresso
ECS deployment tool - deploy, manage, and troubleshoot ECS services.
gateway
Start and manage the Kurtosis gateway for Kubernetes. The gateway forwards local ports to the Kurtosis engine and services running in a k8s cluster. Required when using Kurtosis with Kubernetes. Use when kurtosis engine status shows nothing on k8s or services aren't reachable.
cluster-manage
Manage Kurtosis cluster settings. Switch between Docker and Kubernetes backends, list available clusters, and configure which cluster Kurtosis uses. Use when you need to change where Kurtosis runs enclaves.
aws-collector-tool
AWS infrastructure collector. Fetches ECS status, CloudWatch logs, and metrics. Use when: checking ECS health, inspecting CloudWatch error logs, pulling infra metrics, or monitoring AWS resources.
exec-local-docker
Execute a TensorRT-LLM workload locally in Docker. Runs a fully-resolved Docker command in background, monitors completion, reads logs, and reports results. Workflow-agnostic — does not need to know if the workload is pytest, eval, benchmark, or a custom script.