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 lyarwood/kubevirt-ai-helpers --skill review-enhancementgit clone --depth 1 https://github.com/lyarwood/kubevirt-ai-helpersWrote 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/lyarwood/kubevirt-ai-helpers/review-enhancement)<a href="https://agentmods.dev/skills/lyarwood/kubevirt-ai-helpers/review-enhancement"><img src="https://agentmods.dev/badge/skills/lyarwood/kubevirt-ai-helpers/review-enhancement/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/lyarwood/kubevirt-ai-helpers/review-enhancement"><img src="https://agentmods.dev/badge/skills/lyarwood/kubevirt-ai-helpers/review-enhancement.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 | $0.00055 | $0.05529 |
| Opus 5 | $0.00028 | $0.02764 |
| Sonnet 5 | $0.00011 | $0.01106 |
| Haiku 4.5 | $0.00006 | $0.00553 |
Grade A, and why
review-enhancement 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 8d 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 — 502 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Enhancement
This skill provides the detailed implementation logic for the /kubevirt:review-enhancement command. It covers how to resolve the input (an enhancements PR or a VEP number), read best practices live from the enhancements repo, gather all VEP data sources, perform process compliance checks, execute a multi-pass technical review, verify that updates to existing VEPs stay accurate against their implementation, and produce a structured review report.
When to Use This Skill
- When executing the
/kubevirt:review-enhancementcommand - When a user asks for a comprehensive review of a VEP proposal or an enhancements PR
- When reviewing a VEP graduation / stage-bump PR and needing to confirm the implementation backs it
- When preparing review feedback for a VEP before a SIG meeting or approval decision
Prerequisites
- gh CLI: Must be installed and authenticated (
gh auth status) - Network access: Requires access to the GitHub API for fetching best-practice docs, VEP content, tracking issues, project data, and implementation PRs
Guiding Principle: Best Practices Come From the Repo
Do not rely solely on the checklists baked into this skill. At review time, read the current best practices live from the kubevirt/enhancements repository so the review reflects the process as it stands today. The checks below encode the process as understood when this skill was written; the live docs are authoritative when they differ. See Step 0 for how to load them.
Implementation Steps
Step 0: Resolve Input and Load Best Practices
The command primarily takes an enhancements PR (number or URL), but also accepts a VEP number. Resolve which one was given, then load the live best-practice docs.
0a: Resolve the Input
If the argument is a PR URL or a number that resolves to an open enhancements PR:
gh pr view <pr-number> --repo kubevirt/enhancements --json number,title,body,labels,state,files,url,headRefName,commits
From the PR's changed files, determine the VEP and the kind of change:
- New VEP: the PR adds a
veps/sig-*/NNNN-*/vep.mdfile. - Update to an existing VEP: the PR modifies an existing
veps/sig-*/NNNN-*/vep.md(e.g. a graduation/stage bump or a design change).
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.
- 8d ago Changed · +120 lines · +15 tokens per session d8f6b6e2da23
- 12d ago First seen · 382 lines · 40 tokens per session scan A d72ac608e7c8
review-enhancement is a skill published in the GitHub repository lyarwood/kubevirt-ai-helpers (2 stars, last pushed 10d ago), licensed Apache-2.0. It adds 55 tokens to every session and 5,529 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
autoreview
Pre-commit/ship code review: Codex default; optional Claude or Pi.
omh-code-review
This is a Hermes-native code-review workflow skill.
revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
code-reviewer
Code review specialist focused on patterns, bugs, security, and performance.
full-repo-review
Comprehensive four-wave review of all repo source files, producing a prioritized issue backlog.
agent-teams-simplify-and-harden
Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or…