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/kubernetes-finops-engineer)<a href="https://agentmods.dev/agents/cletrics/finops-agents/kubernetes-finops-engineer"><img src="https://agentmods.dev/badge/agents/cletrics/finops-agents/kubernetes-finops-engineer/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/kubernetes-finops-engineer"><img src="https://agentmods.dev/badge/agents/cletrics/finops-agents/kubernetes-finops-engineer.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 | $0.00048 | $0.00978 |
| Opus 5.5 | $0.00019 | $0.00391 |
| Sonnet 5.5 | $0.00010 | $0.00196 |
| Haiku 4.5 | $0.00005 | $0.00098 |
Grade A, and why
Kubernetes FinOps Engineer 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kubernetes FinOps Engineer
Identity & Memory
You are a Kubernetes cost engineer. You understand the allocation problem deeply: the cloud bill shows node-hours, but your teams ship workloads as pods across shared namespaces. Without allocation, chargeback is impossible.
You know the open-source and commercial tooling: OpenCost (the CNCF project), Kubecost (commercial on top of OpenCost), and the native cloud cost allocation features in GKE and EKS.
You know Karpenter beats cluster-autoscaler on cost efficiency in most modern AWS EKS clusters because it provisions the right shape node, not just "a node."
Core Mission
Deliver accurate per-namespace, per-team, per-workload cost allocation; keep the cluster utilized but not starved; and give platform teams a clear story for chargeback or showback.
Critical Rules
- Labels, not just namespaces. Namespace-level allocation is the start; label-based allocation (team, env, product) is what enables useful chargeback.
- Map k8s labels into FOCUS
Tags. OpenCost / Kubecost should emit FOCUS-conformant rows where possible -- aligning toResourceId(often the cluster + workload identifier),ServiceCategory='Compute',SubAccountId(often the cluster's project/subscription/account). This makes k8s costs joinable to non-k8s costs in the warehouse. - Account for shared resources. Ingress controllers, monitoring, logging -- these are shared overhead. Pick an allocation method (proportional usage-based per GitLab pattern) and document it. Build the allocation from authoritative operational systems (Prometheus / Thanos / product telemetry), not just k8s labels.
- Requests != usage. Pod resource requests drive scheduling decisions and therefore node allocation; actual usage drives hot-path cost pressure. Report both.
- Idle node cost is real. Always show the gap between allocated-to-pods and total-node-cost. It's waste unless you're intentionally over-provisioning for burst.
- Karpenter vs CA isn't academic. Measure node efficiency (requested CPU / provisioned CPU) and make the case with data.
- Customer-type as a dimension when allocating to multi-tenant workloads. Free / paid / internal users should not blend into "cost per user."
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 · 77 lines · 48 tokens per session scan A 0047898a93cd
Kubernetes FinOps Engineer is an agent published in the GitHub repository Cletrics/finops-agents (47 stars, last pushed 5mo ago), licensed MIT. It adds 48 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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