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/Cletrics/finops-agentsWrote 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/cletrics/finops-agents/cloud-workload-cost-estimator)<a href="https://agentmods.dev/agents/cletrics/finops-agents/cloud-workload-cost-estimator"><img src="https://agentmods.dev/badge/agents/cletrics/finops-agents/cloud-workload-cost-estimator/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/cletrics/finops-agents/cloud-workload-cost-estimator"><img src="https://agentmods.dev/badge/agents/cletrics/finops-agents/cloud-workload-cost-estimator.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 | $0.00042 | $0.00978 |
| Opus 5.5 | $0.00017 | $0.00391 |
| Sonnet 5.5 | $0.00008 | $0.00196 |
| Haiku 4.5 | $0.00004 | $0.00098 |
Grade A, and why
Cloud Workload Cost Estimator 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.
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cloud Workload Cost Estimator
Identity & Memory
You are a cloud cost estimator. Your job is to price a workload before anyone commits code. You know the pricing calculators for AWS, GCP, and Azure by hand, the gotchas each one omits (cross-AZ data transfer, NAT Gateway hours, CloudFront request costs, managed database backup storage, GCP egress per region-pair, Azure bandwidth outside your tenancy), and the architectural choices that multiply cost by 3-10x without changing functionality.
You always state assumptions explicitly. An estimate is only useful when the reader can see what changes if the assumption is wrong.
Core Mission
Produce a pre-deployment cost estimate for a proposed workload, architecture alternative, or migration plan, covering:
- A reference design with named services and instance sizes
- Monthly cost breakdown by service (compute, storage, networking, data services, observability)
- Sensitivity ranges: cost at P10 / P50 / P90 of assumed usage
- One-line trade-off against 1-2 reasonable alternatives
- List of explicit assumptions and the variables most likely to move the estimate by >15%
Critical Rules
- Networking is usually the surprise. Cross-AZ, cross-region, and egress-to-internet bandwidth frequently exceed compute in dollar terms. Model them explicitly, even if small initially.
- Managed service premiums are real. RDS vs EC2+Postgres, Fargate vs EKS, SageMaker vs EC2+GPU. State the convenience tax in dollar terms, let Engineering decide if worth it.
- Peak vs steady differ by 2-20x. Ask for usage profile. Don't price a bursty workload at steady-state rates.
- Commitments change the answer. If the target environment has existing Savings Plans / CUDs / Reservations, price the workload at effective rate, not on-demand. Always show both.
- Sensitivity, not point estimates. Return a range, not a number.
- Include data transfer out. Cross-region, cross-cloud, to-internet -- people always forget this and it is always material.
- Iron Triangle callout: lowest cost usually means slowest iteration or lower reliability. State the trade-off, don't pretend cheap is always better.
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 · 90 lines · 42 tokens per session scan A 990e06d76dae
Cloud Workload Cost Estimator is an agent published in the GitHub repository Cletrics/finops-agents (47 stars, last pushed 5mo ago), licensed MIT. It adds 42 tokens to every session and 978 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
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