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 ckanner/agent-skills --skill ui-automationgit clone --depth 1 https://github.com/ckanner/agent-skillsWrote 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/ckanner/agent-skills/ui-automation)<a href="https://agentmods.dev/skills/ckanner/agent-skills/ui-automation"><img src="https://agentmods.dev/badge/skills/ckanner/agent-skills/ui-automation/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/ckanner/agent-skills/ui-automation"><img src="https://agentmods.dev/badge/skills/ckanner/agent-skills/ui-automation.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 | $0.00097 | $0.01564 |
| Opus 5.5 | $0.00039 | $0.00626 |
| Sonnet 5.5 | $0.00019 | $0.00313 |
| Haiku 4.5 | $0.00010 | $0.00156 |
Grade A, and why
ui-automation 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 19d 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
UI Automation (delegated to Codex)
Overview
Dispatch a self-contained task to the external Codex agent when the work requires eyes on a screen or hands on a GUI: browser automation, Chrome inspection, desktop application operation, or visual verification. Codex supplies its own model plus its own browser-use and computer-use plugins. This session supplies the task, the contract, and the review.
The return channel is text only. Screenshots, recordings, and produced files never travel back through it — they must land on disk. The artifact contract below is what makes them retrievable.
When to Use This Skill
- Verifying a deployed or released UI against expected behaviour
- Checking whether a page renders correctly, or inspecting it via browser devtools
- Driving an application that has no usable CLI (a GUI tool, an editor, a 3D package)
- Any task whose success is established by looking at something rather than by reading output
- Any task where the artifact produced (render, export, recording) is the deliverable
Do not use this skill when the task is fully expressible as shell commands and file reads in this workspace — do that work directly.
Do not use this skill to write automation code (test suites, Playwright or Cypress specs, scraping scripts). That is an ordinary coding task. This skill is for dispatching interface work to an external agent, not for producing automation source.
Workflow
Step 1 — Scope the run
Write down, before dispatching:
- the exact URLs, app names, or file paths involved
- the checkable expectations, as a numbered list ("login form shows an error on empty submit")
- what artifacts you need back (screenshots of failures, the exported file, a recording)
Each dispatch is a fresh, self-contained Codex thread. It remembers nothing from a previous dispatch, so everything it needs must be in this prompt or in files on disk.
Step 2 — Prepare the run directory
RUN_ID="$(date +%Y%m%d-%H%M%S)-<slug>"
RUN_DIR="$PWD/.codex-runs/$RUN_ID"
mkdir -p "$RUN_DIR/shots" "$RUN_DIR/out"
cp <skill-dir>/references/output-schema.json "$RUN_DIR/schema.json"
What ships with it
4 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.
- 19d ago First seen · 138 lines · 97 tokens per session scan A 3e91e59b2cfc
ui-automation is a skill published in the GitHub repository ckanner/agent-skills (23 stars, last pushed 19d ago), licensed Apache-2.0. It adds 97 tokens to every session and 1,564 once invoked, about $0.0004 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 2026-10-04.
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