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 skills add gke-labs/kube-agents --skill fleet-auditgit 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/fleet-audit)<a href="https://agentmods.dev/skills/gke-labs/kube-agents/fleet-audit"><img src="https://agentmods.dev/badge/skills/gke-labs/kube-agents/fleet-audit/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/fleet-audit"><img src="https://agentmods.dev/badge/skills/gke-labs/kube-agents/fleet-audit.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 | $0.00033 | $0.12896 |
| Opus 5 | $0.00016 | $0.06448 |
| Sonnet 5 | $0.00007 | $0.02579 |
| Haiku 4.5 | $0.00003 | $0.01290 |
Grade A, and why
fleet-audit scanned grade A with 1 finding 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 today.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
`kubectl`, `gcloud`, `gsutil`, `bq`, `helm`, or `curl`; `echo`, `cat`, `python3 -c`, a call back How it starts
The opening of the file, as written. The whole thing — 819 lines — stays where its author put it; the contents beside it link to each section on GitHub.
fleet-audit — Audit Findings to a Ledger Issue
Every autonomous audit watchdog ends the same way: findings must reach a human somewhere durable, reviewable, and de-duplicated. This skill is that ending, in two tiers:
- Tier 1 — the ledger. Each audit stream owns exactly one open GitHub issue, rewritten in full on every run and closed as completed when the fleet comes back clean. An operator watches one issue per stream instead of drowning in chat logs.
- Tier 2 — the fixes. When a finding's remediation is a file in this repository, it travels separately as a narrow pull request carrying only that fix, linked back to the ledger.
The split is the point. A report is not a change, so a report is not a pull request — and a fix is not a report, so it carries a real diff a reviewer can read in one screen.
./skills/fleet-audit/scripts/audit_report.py owns every deterministic operation: credential
minting, label creation, issue creation and rewriting, branch handling, staging, committing,
pushing, pull-request creation, closing, the run-over-run delta, and every timestamp. Your job is
to inspect the fleet read-only and emit a findings.json. You never hand-write an issue body or a
PR body, never invent a timestamp, and never call gh issue create or gh pr create yourself —
that is precisely why every ledger looks the same and why the delta between runs is computable.
Audit streams
Only these registered audit ids may own a ledger. Any other id is rejected before a single git or gh
command runs. The issue title is [audit] <human name> — <n> findings (<c> critical) (singular
1 finding when there is exactly one), where the human name is the one cron/jobs.json gives that
watchdog — not a prettified form of the audit id:
| Audit id | Rendered ledger title |
|---|---|
compliance-audit |
[audit] Security & RBAC Posture Audit — 7 findings (2 critical) |
security-patch-orchestrator |
[audit] Upgrade & Patch Readiness Audit — 7 findings (2 critical) |
obtainability-audit |
[audit] Workload Reliability Audit — 7 findings (2 critical) |
fleet-wide-cost-analysis |
[audit] Fleet Waste Audit — 7 findings (2 critical) |
fleet-consistency-drift |
[audit] Fleet Consistency Drift Audit — 7 findings (2 critical) |
ai-security-audit |
[audit] AI Workload Security Audit — 7 findings (2 critical) |
stockout-prevention |
[audit] Fleet Stockout Prevention & Capacity Audit — 7 findings (2 critical) |
gcp-networking-fabric-audit |
[audit] GCP Networking Fabric & VPC IPAM Audit — 7 findings (2 critical) |
gce-compute-fleet-audit |
[audit] GCE Compute Engine and MIG Fleet Audit — 7 findings (2 critical) |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- today Changed · +2 lines be1ee91b239b
- 4d ago Changed · +59 lines 4aea708bd40a
- 7d ago Changed · +5 lines c682e15242d2
- 10d ago First seen · 753 lines · 33 tokens per session scan A a7a4108fff0c
fleet-audit is a skill published in the GitHub repository gke-labs/kube-agents (53 stars, last pushed today), licensed Apache-2.0. It adds 33 tokens to every session and 12,896 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
pr-review-triage
Watch open PRs, check CI status, review staleness, merge conflicts, and unanswered review comments. Produces a prioritized watchlist.
issue-creation
Trigger: issue creation, bug reports, feature requests, or issue approval. Create and triage GitHub issues from repository evidence.
sdd-tasks
Break an SDD change into implementation tasks. Trigger: orchestrator launches task planning for a change.
systemic-issue-triage
Trigger: new issue, bug report, triage, backlog, issue flood, community report, root cause, dead-end, blocked user. Attack issues by root class, never one-by-one; fixes must shrink the system, not grow it.
spec-kitty-runtime-review
Review runtime-owned outputs using the Spec Kitty review workflow surface, then direct approval or rejection with structured feedback. Triggers: "review this work package", "check runtime output", "approve this step", "review WP", "is this WP ready to approve", "check this implementation". Does NOT handle: setup-only…
tech-debt
Track, categorize, and prioritize technical debt across the codebase. Scans for debt indicators, maintains a debt register, and recommends repayment scheduling.