Borrowing it
Nothing to install: this file belongs to gke-labs/kube-agents. 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/gke-labs/kube-agents/main/.agents/skills/review-security-k8s-agents-audit-logs/SKILL.mdgit clone --depth 1 https://github.com/gke-labs/kube-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/skills/gke-labs/kube-agents/review-security-k8s-agents-audit-logs)<a href="https://agentmods.dev/skills/gke-labs/kube-agents/review-security-k8s-agents-audit-logs"><img src="https://agentmods.dev/badge/skills/gke-labs/kube-agents/review-security-k8s-agents-audit-logs/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/gke-labs/kube-agents/review-security-k8s-agents-audit-logs"><img src="https://agentmods.dev/badge/skills/gke-labs/kube-agents/review-security-k8s-agents-audit-logs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00029 | $0.00274 |
| Opus 5 | $0.00015 | $0.00137 |
| Sonnet 5 | $0.00006 | $0.00055 |
| Haiku 4.5 | $0.00003 | $0.00027 |
Grade A, and why
review-security-k8s-agents-audit-logs 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.
What it actually says
Task
Review manifests, logging architecture, and agent configs to guarantee tamper-proof, comprehensive logging of AI agent activities.
Checks
1. API Audit Coverage
- Isolation: Require dedicated
ServiceAccountper agent. Flag shared ordefaultaccounts. - Audit Policy: Ensure
AuditPolicycaptures all agent API requests (minimumMetadatalevel, preferRequestResponsefor mutations).
2. Tamper-Proof Architecture
- Standard Streams: Require logging to
stdout/stderr. Flag local disk logging. - Log Isolation: Agents MUST NOT have read/write/delete access to aggregated logs. Flag
hostPathmounts to/var/log/containersor/var/log/pods.
3. Prompt & Output Auditing
- Telemetry: Ensure deep application logging is enabled for full LLM prompts and raw outputs.
- Tool Execution: Require exact input/output logging for all invoked tools (e.g. CLI, HTTP).
- Data Scrubbing: Require scrubbing/masking of sensitive data (PII, secrets) before logs are written.
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 · 21 lines · 29 tokens per session scan A 8ebd25c027c8
review-security-k8s-agents-audit-logs is a skill published in the GitHub repository gke-labs/kube-agents (54 stars, last pushed today), licensed Apache-2.0. It adds 29 tokens to every session and 274 once invoked, about $0.0001 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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