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 agentmods add skills/vinhnx/vtcode/cmd-reviewnpx skills add vinhnx/VTCode --skill cmd-reviewgit clone --depth 1 https://github.com/vinhnx/VTCodeWhat 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 | $0.00040 | $0.00225 |
| Opus 5 | $0.00020 | $0.00112 |
| Sonnet 5 | $0.00008 | $0.00045 |
| Haiku 4.5 | $0.00004 | $0.00022 |
Grade A, and why
cmd-review 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 2d 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
Review Changes
Interpret the user input as the raw argument string that follows /review.
- Support the existing slash-style review inputs such as
--last-diff,--target <expr>,--file <path>, positional file paths, and--style <style>. - If the input is empty, review the current diff.
- Focus on bugs, regressions, correctness risks, and missing tests before any summary.
- Use concrete file and line references when you identify a finding.
- Keep findings ordered by severity and keep the high-level summary brief.
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.
- 2d ago First seen · 21 lines · 40 tokens per session scan A ffe4a1531aea
cmd-review is a skill published in the GitHub repository vinhnx/VTCode (825 stars, last pushed 2d ago), licensed Apache-2.0. It adds 40 tokens to every session and 225 once invoked, about $0.0002 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.
Other skills, from other repositories
unifly
This skill should be used when the user asks to "manage UniFi devices", "configure UniFi networks", "create a VLAN", "provision an SSID", "create firewall rules", "reorder firewall policies", "create a NAT rule", "set up port forwarding", "configure masquerade NAT", "add DNS records", "manage traffic matching lists"…
verify
Drive an engine app headlessly in a pty, record a video of the whole verification, and open a summary page (video + timeline + checks) with pixel open.
claude-api
Build, debug, and optimize Claude API / Anthropic SDK apps. Apps built with this skill should include prompt caching. Also handles migrating existing Claude API code between Claude model versions (4.5 → 4.6, 4.6 → 4.7, retired-model replacements). TRIGGER when: code imports anthropic/@anthropic-ai/sdk; user asks for…
harbor
Run Terminal-Bench or any Harbor dataset with Ante as the agent, using the Harbor adapter in the ante repo's ante-harbor/ directory. Use when the user wants to benchmark Ante on Harbor or reproduce Ante's published eval results.
gui-onboarding-verification-skill
GUI desktop app only. Launch two parallel Oz cloud agents with computer use to download and install the latest stable Linux Warp build, capture screenshots while walking through first-time onboarding in both logged-out and logged-in states, then selectively fan out follow-up cloud agents for distinct onboarding…
create-skill
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.