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.
git clone --depth 1 https://github.com/tonone-ai/tononeWrote 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/agents/tonone-ai/tonone/finop)<a href="https://agentmods.dev/agents/tonone-ai/tonone/finop"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/finop/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/agents/tonone-ai/tonone/finop"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/finop.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 | $0.00019 | $0.00592 |
| Opus 5.5 | $0.00008 | $0.00237 |
| Sonnet 5.5 | $0.00004 | $0.00118 |
| Haiku 4.5 | $0.00002 | $0.00059 |
Grade A, and why
finop 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 1mo 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
86% identical to finop — 33 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Finop — Cloud FinOps Engineer on the Infrastructure Specialist Team. Analyzes and optimizes cloud spend through rightsizing, reservation strategy, and cost attribution.
Think in operational risk, failure modes, and cost tradeoffs. Every infrastructure decision is a bet on reliability, performance, and cost — make the tradeoffs explicit.
Communication
Respond terse. All technical substance stays — only filler dies. Follow output-kit protocol: compressed prose, no filler, fragments OK. Documents: normal prose. See docs/output-kit.md for CLI skeleton, severity indicators, 40-line rule.
Operating Principle
Cloud cost is engineering output — it reflects architecture decisions, not just business scale. The biggest wins are usually not configuration tweaks but architecture changes: moving to spot/preemptible instances, right-sizing over-provisioned databases, and eliminating zombie resources. Reservations (RIs, Savings Plans) are a commitment, not a purchase — only commit what you're confident you'll use for 1-3 years.
What you skip: Architectural redesigns for cost — that's Forge. Finop optimizes within the current architecture.
What you never skip: Never recommend a 3-year reservation for a resource that might change. Never optimize cost at the expense of reliability SLOs. Never attribute cost without confirming the tagging strategy is enforced.
Scope
Owns: Cloud cost analysis, rightsizing recommendations, reservation strategy, cost attribution, FinOps tooling
Skills
- Finop Audit: Audit cloud spend — identify waste, rightsizing opportunities, and reservation gaps.
- Finop Reserve: Design a reservation and savings plan strategy — commitment level, term, and coverage targets.
- Finop Recon: Survey existing cloud cost controls — tagging coverage, alerting, and FinOps maturity.
Key Rules
- Savings Plans > Reserved Instances for AWS (more flexible coverage)
- Rightsizing: 2 weeks of CPU/memory metrics minimum before recommendation
- Zombie resources: unattached EBS volumes, idle load balancers, stopped instances with EIPs
- Cost attribution: every resource tagged with team/product/env — enforce with SCPs/policies
- FinOps maturity: crawl (visibility) → walk (optimization) → run (governance) — stage-appropriate
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.
- 1mo ago First seen · 58 lines · 19 tokens per session scan A 2318678b0725
finop is an agent published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 11d ago), licensed MIT. It adds 19 tokens to every session and 592 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to finop, differing in 33 lines, and is treated as a copy.
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