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 X-School-Academy/skill-pilot --skill find-ui-elementgit clone --depth 1 https://github.com/X-School-Academy/skill-pilotWrote 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/x-school-academy/skill-pilot/find-ui-element)<a href="https://agentmods.dev/skills/x-school-academy/skill-pilot/find-ui-element"><img src="https://agentmods.dev/badge/skills/x-school-academy/skill-pilot/find-ui-element/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/x-school-academy/skill-pilot/find-ui-element"><img src="https://agentmods.dev/badge/skills/x-school-academy/skill-pilot/find-ui-element.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 | $0.00054 | $0.01480 |
| Opus 5.5 | $0.00022 | $0.00592 |
| Sonnet 5.5 | $0.00011 | $0.00296 |
| Haiku 4.5 | $0.00005 | $0.00148 |
Grade A, and why
find-ui-element 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 16d 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Builder - Find UI Element
Locate any clickable or interactive UI element in a screenshot — buttons, links, dropdowns, checkboxes, radio buttons, text input areas, etc. Uses a vision-first approach:
- find quickly from the full image,
- verify with a small close-up crop,
- if wrong, retry with fixed-grid crops in nearby regions.
When to Use This Skill
- Locating any clickable element (button, link, dropdown, checkbox, radio button) in a screenshot
- Finding text input areas (search boxes, form fields, text areas) for typing automation
- Getting pixel coordinates of a UI element for computer-use tasks
- Verifying element positions before automated interaction
Your Roles in This Skill
- QA Engineer: Visually inspect screenshots, locate target elements, and verify bounding box accuracy.
Role Communication
As an expert in your assigned roles, you must announce your actions before performing them using the following format:
As a {Role}, I will {action description}
This communication pattern ensures transparency and allows for human-in-the-loop oversight at key decision points.
Instructions
Follow these steps in order.
Retry policy:
MAX_TRIES = 4total attempts (1 initial + up to 3 retries)- Stop early when the verification crop clearly confirms the element
- If all tries fail, report failure explicitly (element may be absent or not visually identifiable)
Step 1: Load and View the Screenshot
Load the screenshot and note its dimensions. Then visually inspect the full image to estimate where the target element is.
core/bin/python -c "from PIL import Image; img = Image.open('INPUT_PATH'); print(f'Dimensions: {img.size[0]}x{img.size[1]}')"
Step 2: Estimate Coordinates by Vision
Look at the full screenshot and estimate the bounding box (x1, y1, x2, y2) of the target element based on visual inspection. Use the image dimensions to guide your estimate.
Step 3: Draw and Verify (Small Area First)
Draw the bounding box, then crop around it to verify.
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.
- 16d ago First seen · 124 lines · 54 tokens per session scan A 97083e8fe7af
find-ui-element is a skill published in the GitHub repository X-School-Academy/skill-pilot (20 stars, last pushed 4mo ago), licensed MIT. It adds 54 tokens to every session and 1,480 once invoked, about $0.0002 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 2026-10-02.
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