Borrowing it
Nothing to install: this file belongs to lglucas/ai-dev-operating-system. 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/lglucas/ai-dev-operating-system/main/.claude/skills/usage-monitor/SKILL.mdgit clone --depth 1 https://github.com/lglucas/ai-dev-operating-systemWrote 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/lglucas/ai-dev-operating-system/usage-monitor)<a href="https://agentmods.dev/skills/lglucas/ai-dev-operating-system/usage-monitor"><img src="https://agentmods.dev/badge/skills/lglucas/ai-dev-operating-system/usage-monitor/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/lglucas/ai-dev-operating-system/usage-monitor"><img src="https://agentmods.dev/badge/skills/lglucas/ai-dev-operating-system/usage-monitor.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 | $0.00068 | $0.00803 |
| Opus 5 | $0.00034 | $0.00402 |
| Sonnet 5 | $0.00014 | $0.00161 |
| Haiku 4.5 | $0.00007 | $0.00080 |
Grade A, and why
usage-monitor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Usage Monitor
When to run this skill
- 24h after a public launch.
- Weekly during the first month after launch.
- Whenever the user asks "quanto tá custando" / "tô gastando muito" / "como tá a fatura".
- After a feature that calls a metered service ships.
- When a billing alert fires.
Dashboard format
📊 Usage & cost — last 7 days
🤖 LLM (Anthropic):
Input tokens: 1.2M (R$ 9.00)
Output tokens: 340K (R$ 17.00)
Cache reads: 800K (R$ 0.60)
Total: R$ 26.60
Per active user: R$ 0.27
⚠️ Up 340% vs prev week — investigate.
☁️ Hosting (Vercel):
Bandwidth: 4.2 GB / 100 GB free
Function invocations: 22K / 100K free
Status: 🟢 within free tier
🗄️ Database (Supabase):
DB size: 142 MB / 500 MB free
Active users (mau): 18 / 50K free
Status: 🟢 within free tier
✉️ Email (Resend):
Sent: 240 / 3000 free
Status: 🟢 within free tier
💰 Total billable this week: R$ 26.60
🔮 Projected month: R$ 114
Sources of truth
- Anthropic: Console → Billing → Usage. API:
/v1/organizations/usage_report. - Vercel: Dashboard → Usage tab.
- Supabase: Dashboard → Project Settings → Usage.
- Resend: Dashboard → Logs.
- Stripe: Dashboard → Reports.
If the user hasn't connected a usage API: "para automatizar, preciso da chave read-only da [provider]. Sem ela, eu te lembro de checar manualmente toda segunda."
Triggers for action
| Sinal | Ação recomendada |
|---|---|
| LLM custo / usuário ativo > R$ 1 | Revisar prompts, considerar Haiku, ativar cache. |
| Bandwidth > 70% do free tier | Auditar imagens grandes, downloads. |
| DB > 70% do free tier | Auditar tabelas grandes, archive. |
| Spike > 200% week-over-week | Investigar imediatamente — provável loop / abuse. |
| Erro de cobrança / cartão recusado | Avisar usuário no chat. |
Vibe coder explanation
Imagina que cada serviço que você usa tem um relógio rodando. Toda semana eu olho os relógios pra você e falo: "tudo OK", "tá perto do limite", ou "tem algo estranho". Você não precisa entrar em 5 dashboards.
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.
- 12d ago First seen · 81 lines · 68 tokens per session scan A c5f028dc96c9
usage-monitor is a skill published in the GitHub repository lglucas/ai-dev-operating-system (11 stars, last pushed 1mo ago), licensed MIT. It adds 68 tokens to every session and 803 once invoked, about $0.0003 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 2026-08-30.
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