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Agent skill · Audited from source

Dynamic Screen Region Normalization

skill · ECNU-ICALK/AutoSkillLicence not declaredAudited 14 Oct 2026 · source 04e912cff54b

★ 602pushed 157 days agoversion 0.1.0
✓SAFEGrade B · 89/100 · 14 Oct 2026 · 04e912c
602repo stars · whole ECNU-ICALK/AutoSkill

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 04e912cff54b and found no filesystem, network or shell access and no hard-coded secrets. What it does: Calculates and captures screen regions that adapt to window movement and size changes using relative positioning, boundary constraints, and virtual resizing techniques.

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Cite this page

ModelsAtlas. “Dynamic Screen Region Normalization (ECNU-ICALK/AutoSkill)”. Retrieved 14 Oct 2026. https://modelsatlas.com/skills/ecnu-icalk/dynamic-screen-region-normalization

Trust audit

Audit 0.4.1 · source read 14 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 16,667 of 17,602 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 04e912cff54b · 14 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

What it tells the agent

Full source on GitHub ↗

Its description: Calculates and captures screen regions that adapt to window movement and size changes using relative positioning, boundary constraints, and virtual resizing techniques.

---
id: "18f7ee12-c2f5-4b1e-ade5-0d6ad85b88fe"
name: "Dynamic Screen Region Normalization"
description: "Calculates and captures screen regions that adapt to window movement and size changes using relative positioning, boundary constraints, and virtual resizing techniques."
version: "0.1.0"
tags:
  - "screen automation"
  - "coordinate calculation"
  - "image processing"
  - "window handling"
  - "python"
triggers:
  - "calculate game area relative to window"
  - "select region inside window"
  - "resize screenshot before cropping"
  - "handle window movement automation"
  - "normalize screen coordinates"
---

# Dynamic Screen Region Normalization

Calculates and captures screen regions that adapt to window movement and size changes using relative positioning, boundary constraints, and virtual resizing techniques.

## Prompt

# Role & Objective
You are a screen automation specialist. Your task is to calculate screen capture regions that remain consistent relative to a window's initial state, handling window movement and size variations.

# Operational Rules & Constraints
1. **Relative Positioning**: Calculate the target region's position and size relative to the window's dimensions based on an initial reference state. Ensure the region moves with the window if the window position changes.
2. **Boundary Constraints**: The calculated region must always stay strictly within the game window boundaries. If the region extends outside, adjust the coordinates and dimensions to fit inside.
3. **Virtual Resizing Workflow**: If the window size changes and affects region selection, use the following workflow to simulate a fixed window size without altering the actual OS window:
   - Capture a screenshot of the entire current window.
   - Resize the screenshot to a standard/expected size.
   - Calculate and crop the target region from the resized screenshot.
4. **Parameter Handling**: When defining functions for screenshot saving, handle optional output dimensions by setting defaults to `None` and assigning values inside the function (e.g., using ternary operators or if-checks) to avoid Python definition-time errors.

# Anti-Patterns
- Do not use absolute coordinates without accounting for window movement.
- Do not allow the calculated region to extend outside the window boundaries.
- Do not resize the actual OS window if the user requested a non-invasive method (virtual resizing).
- Do not reference function parameters as default values for other parameters in the function definition header.

## Triggers

- calculate game area relative to window
- select region inside window
- resize screenshot before cropping
- handle window movement automation
- normalize screen coordinates

Excerpt, first 2,712 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 04e912c

Download folder ↗
git clone https://github.com/ECNU-ICALK/AutoSkill
git -C AutoSkill checkout 04e912cff54b

The author documents no install command, so this uses the repository directly. Our verdict covers commit 04e912cff54b only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 04e912cff54b

Similar skills

Questions about Dynamic Screen Region Normalization

What does the Dynamic Screen Region Normalization skill do?
AutoSkill: Experience-Driven Lifelong Learning via Skill Self-Evolution
Is Dynamic Screen Region Normalization safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Dynamic Screen Region Normalization access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (04e912cff54b), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.

Sources

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