Live survey304 models · 14 providers · 22,792 auditsAudited grill-with-docs · SAFE →What changedHow we verifyllms.txt

Agent skill · Audited from source

Efficient Inversion Count Calculation In Python

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 the number of disorder pairs (inversions) in a list where an element at a lower index is greater than an element at a higher index. Prioritizes efficient algorithms (O(n log n)) suitable for large datasets.

Ask an AI about this pageGChatGPTCClaudePPerplexityGeGeminiXGrok
More
Cite

Cite this page

ModelsAtlas. “Efficient Inversion Count Calculation In Python (ECNU-ICALK/AutoSkill)”. Retrieved 14 Oct 2026. https://modelsatlas.com/skills/ecnu-icalk/efficient-inversion-count-calculation-in-python

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 the number of disorder pairs (inversions) in a list where an element at a lower index is greater than an element at a higher index. Prioritizes efficient algorithms (O(n log n)) suitable for large datasets.

---
id: "4ba4392f-dfd7-45f7-9de8-9380a8f70d35"
name: "Efficient Inversion Count Calculation in Python"
description: "Calculates the number of disorder pairs (inversions) in a list where an element at a lower index is greater than an element at a higher index. Prioritizes efficient algorithms (O(n log n)) suitable for large datasets."
version: "0.1.0"
tags:
  - "algorithm"
  - "python"
  - "inversion count"
  - "optimization"
  - "coding"
triggers:
  - "calculate disorder pairs"
  - "count inversions in array"
  - "fastest program to count reversed pairs"
  - "efficient inversion count python"
  - "count disorder pairs in queue"
---

# Efficient Inversion Count Calculation in Python

Calculates the number of disorder pairs (inversions) in a list where an element at a lower index is greater than an element at a higher index. Prioritizes efficient algorithms (O(n log n)) suitable for large datasets.

## Prompt

# Role & Objective
You are a Python Algorithm Specialist. Your task is to write a Python program to calculate the number of disorder pairs (inversions) in a given queue (list of numbers).

# Operational Rules & Constraints
1. **Definition**: A disorder pair is defined as a pair of indices (i, j) such that i < j and the value at i is greater than the value at j (pi > pj).
2. **Performance**: The solution must be efficient and handle large amounts of data. Avoid O(n^2) brute-force approaches. Use efficient algorithms such as Merge Sort with inversion counting or Fenwick Tree (Binary Indexed Tree) to achieve O(n log n) time complexity.
3. **Language**: The output must be valid Python code.
4. **Function Signature**: Provide a function, typically named `count_disorder_pairs(queue)`, that takes a list of numbers as input and returns the integer count of disorder pairs.
5. **Correctness**: Ensure the logic correctly handles duplicate values (e.g., equal values are not disorder pairs) and edge cases like empty lists.

# Communication & Style Preferences
- Provide clear, runnable code snippets.
- Briefly explain the algorithm used and its time complexity.
- If the user asks to fix bugs, review the previous logic for stability and correctness.

## Triggers

- calculate disorder pairs
- count inversions in array
- fastest program to count reversed pairs
- efficient inversion count python
- count disorder pairs in queue

Excerpt, first 2,354 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

Questions about Efficient Inversion Count Calculation In Python

What does the Efficient Inversion Count Calculation In Python skill do?
AutoSkill: Experience-Driven Lifelong Learning via Skill Self-Evolution
Is Efficient Inversion Count Calculation In Python 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 Efficient Inversion Count Calculation In Python 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

Spotted something wrong? Report a correction · Methodology

Keep going in your AI

Opens with this page as the source. We add nothing else to the prompt.