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/rockielab/rockie-codex/gpu-spendnpx skills add Rockielab/rockie-codex --skill gpu-spendgit clone --depth 1 https://github.com/Rockielab/rockie-codexWrote 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/rockielab/rockie-codex/gpu-spend)<a href="https://agentmods.dev/skills/rockielab/rockie-codex/gpu-spend"><img src="https://agentmods.dev/badge/skills/rockielab/rockie-codex/gpu-spend.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 | $0.00000 | $0.00871 |
| Opus 5 | $0.00000 | $0.00436 |
| Sonnet 5 | $0.00000 | $0.00174 |
| Haiku 4.5 | $0.00000 | $0.00087 |
Grade A, and why
gpu-spend 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.
This is a copy
100% identical to gpu-spend — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: gpu-spend
description: When the user (or you) needs to know GPU spend — "what's my burn rate?", "how much have I spent this week?", "is anything still running?", "am I close to budget?", "what's running idle?" — invoke this. Wraps rockie-gpu spent --json (the deidentified Rockie-GPU spend surface) for accurate, reconciled numbers, then summarizes for the user. rockie-gpu is the single GPU surface: it never names the underlying compute supplier and never exposes a supplier API key. Custom-mode users: if ROCKIE_GPU_MODE=custom, invoke /gpu-custom instead — rockie-gpu is bypassed in that mode.
/gpu-spend — Rockie-GPU spend snapshot
The single source of truth for "what is the agent costing me right now?"
rockie-gpu spent reconciles live state, sums project spend, and prints
both the LLM-readable JSON and a human view — all under Rockie's own
deidentified billing surface, with no supplier names and no supplier
billing URLs leaking through.
When to invoke
- User asks anything about cost, spend, rate, burn, budget, or pods running.
- Before any decision to spin up a new GPU (read state before adding load).
- After terminating a pod, to confirm the bleed has stopped.
- Periodically during long autonomous runs (the budget-reconcile.sh hook fires this on every UserPromptSubmit, but the agent should also check on entering the Codify phase).
Do NOT invoke if the user asked a non-cost question and you'd just be showing off. The hook keeps the budget honest in the background.
What the skill does
Runs:
rockie-gpu spent --json
Output shape (LLM-ergonomic, deidentified — Rockie-priced, no supplier names):
{
"project": "...",
"compute_per_hr": 0.0,
"storage_per_hr": 0.011,
"running_pods": 0,
"idle_volume_gb": 80,
"grand_total_per_hr": 0.011,
"grand_cumulative_usd": 2.20
}
Read the JSON. Synthesize a 2–3 line summary for the user that:
- Names the top spend driver (compute or storage).
- Calls out idle storage if
running_pods=0butidle_volume_gb > 0(user is paying for nothing — recommend tearing the pod down). - Compares
grand_cumulative_usdto budget ceiling if known (rockie-gpu spent --jsonreports the ceiling when one is configured).
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 · 83 lines · 0 tokens per session scan A cc9f3e52e9ec
gpu-spend is a skill published in the GitHub repository Rockielab/rockie-codex (20 stars, last pushed 1mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 871 tokens. A static security scan graded it A with 0 findings. It is 100% identical to gpu-spend, differing in 0 lines, and is treated as a copy.
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